Index

$ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z _
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

$

$ - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Punctuation $

$(String) - Static method in interface smile.data.formula.Terms

Creates a variable.

A

a - Variable in class smile.validation.metric.ContingencyTable

The row sum of contingency table.

aat() - Method in class smile.math.matrix.BigMatrix

Returns A * A'.

aat() - Method in class smile.math.matrix.fp32.Matrix

Returns A * A'.

aat() - Method in class smile.math.matrix.fp32.SparseMatrix

Returns A * A'.

aat() - Method in class smile.math.matrix.Matrix

Returns A * A'.

aat() - Method in class smile.math.matrix.SparseMatrix

Returns A * A'.

Abbreviations - Interface in smile.nlp.dictionary

A dictionary interface for abbreviations.

abs() - Method in class smile.math.Complex

Returns the abs/modulus/magnitude.

abs(String) - Static method in interface smile.data.formula.Terms

The abs(x) term.

abs(Term) - Static method in interface smile.data.formula.Terms

The abs(x) term.

Abs - Class in smile.data.formula

The term of abs function.

Abs(Term) - Constructor for class smile.data.formula.Abs

Constructor.

AbstractBiFunction - Class in smile.data.formula

This class provides a skeletal implementation of the bi-function term.

AbstractBiFunction(String, Term, Term) - Constructor for class smile.data.formula.AbstractBiFunction

Constructor.

AbstractClassifier<T> - Class in smile.classification

Abstract base class of classifiers.

AbstractClassifier(int[]) - Constructor for class smile.classification.AbstractClassifier

Constructor.

AbstractClassifier(BaseVector<?, ?, ?>) - Constructor for class smile.classification.AbstractClassifier

Constructor.

AbstractClassifier(IntSet) - Constructor for class smile.classification.AbstractClassifier

Constructor.

AbstractFunction - Class in smile.data.formula

This class provides a skeletal implementation of the function term.

AbstractFunction(String, Term) - Constructor for class smile.data.formula.AbstractFunction

Constructor.

AbstractInterpolation - Class in smile.interpolation

Abstract base class of one-dimensional interpolation methods.

AbstractInterpolation(double[], double[]) - Constructor for class smile.interpolation.AbstractInterpolation

Constructor.

AbstractTuple - Class in smile.data

Abstract tuple base class.

AbstractTuple() - Constructor for class smile.data.AbstractTuple

accept(int, int, double) - Method in interface smile.math.matrix.DoubleConsumer

Accepts one matrix element and performs the operation on the given arguments.

accept(int, int, float) - Method in interface smile.math.matrix.fp32.FloatConsumer

Accepts one matrix element and performs the operation on the given arguments.

accept(File) - Method in class smile.swing.FileChooser.SimpleFileFilter

accuracy - Variable in class smile.validation.ClassificationMetrics

The accuracy on validation data.

Accuracy - Class in smile.deep.metric

The accuracy is the proportion of true results (both true positives and true negatives) in the population.

Accuracy - Class in smile.validation.metric

The accuracy is the proportion of true results (both true positives and true negatives) in the population.

Accuracy() - Constructor for class smile.deep.metric.Accuracy

Constructor.

Accuracy() - Constructor for class smile.validation.metric.Accuracy

Accuracy(double) - Constructor for class smile.deep.metric.Accuracy

Constructor.

acf(double[], int) - Static method in interface smile.timeseries.TimeSeries

Autocorrelation function.

acos() - Method in class smile.deep.tensor.Tensor

Returns a new tensor with the arccosine of the elements of input.

acos(String) - Static method in interface smile.data.formula.Terms

The acos(x) term.

acos(Term) - Static method in interface smile.data.formula.Terms

The acos(x) term.

acos_() - Method in class smile.deep.tensor.Tensor

Computes the arccosine of the elements of input in place.

actionPerformed(ActionEvent) - Method in class smile.plot.swing.PlotGrid

actionPerformed(ActionEvent) - Method in class smile.swing.table.ButtonCellRenderer

actionPerformed(ActionEvent) - Method in class smile.swing.table.ColorCellEditor

actionPerformed(ActionEvent) - Method in class smile.swing.table.FontCellEditor

actionPerformed(ActionEvent) - Method in class smile.swing.table.TableCopyPasteAdapter

This method is activated on the Keystrokes we are listening to in this implementation.

activation() - Method in record class smile.llm.Transformer.Options

Returns the value of the activation record component.

activation() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns the value of the activation record component.

ActivationFunction - Class in smile.deep.activation

The activation function.

ActivationFunction - Interface in smile.base.mlp.activation

The activation function.

ActivationFunction - Interface in smile.base.mlp

The activation function in hidden layers.

ActivationFunction(String, boolean) - Constructor for class smile.deep.activation.ActivationFunction

Constructor.

AdaBoost - Class in smile.classification

AdaBoost (Adaptive Boosting) classifier with decision trees.

AdaBoost(Formula, int, DecisionTree[], double[], double[], double[]) - Constructor for class smile.classification.AdaBoost

Constructor.

AdaBoost(Formula, int, DecisionTree[], double[], double[], double[], IntSet) - Constructor for class smile.classification.AdaBoost

Constructor.

Adam - Class in smile.base.mlp.optimizer

Adaptive Moment optimizer.

Adam() - Constructor for class smile.base.mlp.optimizer.Adam

Constructor.

Adam(TimeFunction) - Constructor for class smile.base.mlp.optimizer.Adam

Constructor.

Adam(TimeFunction, double, double) - Constructor for class smile.base.mlp.optimizer.Adam

Constructor.

Adam(TimeFunction, double, double, double) - Constructor for class smile.base.mlp.optimizer.Adam

Constructor.

Adam(Model, double) - Static method in class smile.deep.Optimizer

Returns an Adam optimizer.

Adam(Model, double, double, double, double, double, boolean) - Static method in class smile.deep.Optimizer

Returns an Adam optimizer.

AdamW(Model, double) - Static method in class smile.deep.Optimizer

Returns an AdamW optimizer.

AdamW(Model, double, double, double, double, double, boolean) - Static method in class smile.deep.Optimizer

Returns an AdamW optimizer.

adaptiveAvgPool2d(int) - Static method in interface smile.deep.layer.Layer

Returns an adaptive average pooling layer.

AdaptiveAvgPool2dLayer - Class in smile.deep.layer

An adaptive average pooling that reduces a tensor by combining cells.

AdaptiveAvgPool2dLayer(int) - Constructor for class smile.deep.layer.AdaptiveAvgPool2dLayer

Constructor.

AdaptiveAvgPool2dLayer(int, int) - Constructor for class smile.deep.layer.AdaptiveAvgPool2dLayer

Constructor.

adb(Transpose, BigMatrix, double[], Transpose, BigMatrix) - Static method in class smile.math.matrix.BigMatrix

Returns A * D * B, where D is a diagonal matrix.

adb(Transpose, Matrix, float[], Transpose, Matrix) - Static method in class smile.math.matrix.fp32.Matrix

Returns A * D * B, where D is a diagonal matrix.

adb(Transpose, Matrix, double[], Transpose, Matrix) - Static method in class smile.math.matrix.Matrix

Returns A * D * B, where D is a diagonal matrix.

add(double) - Method in class smile.deep.tensor.Tensor

Returns A + b.

add(double) - Method in class smile.math.matrix.BigMatrix

A += b

add(double) - Method in class smile.math.matrix.Matrix

A += b

add(double) - Method in class smile.sort.DoubleHeapSelect

Assimilate a new value from the stream.

add(double) - Method in class smile.sort.IQAgent

Assimilate a new value from the stream.

add(double) - Method in class smile.util.Array2D

A += x.

add(double) - Method in class smile.util.DoubleArrayList

Appends the specified value to the end of this list.

add(double...) - Method in class smile.plot.swing.Isoline

Add a point to the contour line.

add(double[]) - Method in class smile.util.DoubleArrayList

Appends an array to the end of this list.

add(double[], double[]) - Static method in class smile.math.MathEx

Element-wise sum of two arrays y = x + y.

add(double, double[], double[]) - Method in class smile.math.matrix.BigMatrix

Rank-1 update A += alpha * x * y'

add(double, double[], double[]) - Method in class smile.math.matrix.Matrix

Rank-1 update A += alpha * x * y'

add(double, double, BigMatrix) - Method in class smile.math.matrix.BigMatrix

Element-wise addition A = alpha * A + beta * B

add(double, double, Matrix) - Method in class smile.math.matrix.Matrix

Element-wise addition A = alpha * A + beta * B

add(double, BigMatrix) - Method in class smile.math.matrix.BigMatrix

Element-wise addition A += beta * B

add(double, BigMatrix, double, BigMatrix) - Method in class smile.math.matrix.BigMatrix

Element-wise addition C = alpha * A + beta * B

add(double, Matrix) - Method in class smile.math.matrix.Matrix

Element-wise addition A += beta * B

add(double, Matrix, double, Matrix) - Method in class smile.math.matrix.Matrix

Element-wise addition C = alpha * A + beta * B

add(float) - Method in class smile.deep.tensor.Tensor

Returns A + b.

add(float) - Method in class smile.math.matrix.fp32.Matrix

A += b

add(float) - Method in class smile.sort.FloatHeapSelect

Assimilate a new value from the stream.

add(float, float[], float[]) - Method in class smile.math.matrix.fp32.Matrix

Rank-1 update A += alpha * x * y'

add(float, float, Matrix) - Method in class smile.math.matrix.fp32.Matrix

Element-wise addition A = alpha * A + beta * B

add(float, Matrix) - Method in class smile.math.matrix.fp32.Matrix

Element-wise addition A += beta * B

add(float, Matrix, float, Matrix) - Method in class smile.math.matrix.fp32.Matrix

Element-wise addition C = alpha * A + beta * B

add(int) - Method in class smile.neighbor.lsh.Bucket

Adds a point to bucket.

add(int) - Method in class smile.sort.IntHeapSelect

Assimilate a new value from the stream.

add(int) - Method in class smile.util.IntArray2D

A += x.

add(int) - Method in class smile.util.IntArrayList

Appends the specified value to the end of this list.

add(int) - Method in class smile.util.IntHashSet

Adds the specified element to this set if it is not already present.

add(int...) - Method in class smile.util.IntArrayList

Appends an array to the end of this list.

add(int, double[]) - Method in class smile.neighbor.lsh.Hash

Insert an item into the hash table.

add(int, double[]) - Method in class smile.neighbor.lsh.MultiProbeHash

add(int, int, double) - Method in class smile.math.matrix.BigMatrix

A[i,j] += b

add(int, int, double) - Method in class smile.math.matrix.Matrix

A[i,j] += b

add(int, int, double) - Method in class smile.util.Array2D

A[i, j] += x.

add(int, int, float) - Method in class smile.math.matrix.fp32.Matrix

A[i,j] += b

add(int, int, int) - Method in class smile.util.IntArray2D

A[i, j] += x.

add(String, double) - Method in class smile.hpo.Hyperparameters

Adds a parameter.

add(String, double[]) - Method in class smile.hpo.Hyperparameters

Adds a parameter.

add(String, double, double) - Method in class smile.hpo.Hyperparameters

Adds a parameter.

add(String, double, double, double) - Method in class smile.hpo.Hyperparameters

Adds a parameter.

add(String, int) - Method in class smile.hpo.Hyperparameters

Adds a parameter.

add(String, int[]) - Method in class smile.hpo.Hyperparameters

Adds a parameter.

add(String, int, int) - Method in class smile.hpo.Hyperparameters

Adds a parameter.

add(String, int, int, int) - Method in class smile.hpo.Hyperparameters

Adds a parameter.

add(String, String) - Static method in interface smile.data.formula.Terms

Adds two terms.

add(String, String) - Method in class smile.hpo.Hyperparameters

Adds a parameter.

add(String, String[]) - Method in class smile.hpo.Hyperparameters

Adds a parameter.

add(String, Module) - Method in class smile.deep.layer.LayerBlock

Adds a sub-layer.

add(String, Term) - Static method in interface smile.data.formula.Terms

Adds two terms.

add(String, Layer) - Method in class smile.deep.layer.LayerBlock

Adds a sub-layer.

add(String, T) - Method in class smile.hash.PerfectMap.Builder

Add a new key-value pair.

add(Map<K, V>) - Method in class smile.neighbor.BKTree

Adds a dataset into BK-tree.

add(K, V) - Method in class smile.neighbor.BKTree

Adds a datum into the BK-tree.

add(Term, String) - Static method in interface smile.data.formula.Terms

Adds two terms.

add(Term, Term) - Static method in interface smile.data.formula.Terms

Adds two terms.

add(Layer) - Method in class smile.deep.layer.SequentialBlock

Adds a layer to the sequential block.

add(Tensor) - Method in class smile.deep.tensor.Tensor

Returns A + B.

add(Tensor, double) - Method in class smile.deep.tensor.Tensor

Returns A + alpha * B.

add(Complex) - Method in class smile.math.Complex

Returns this + b.

add(BigMatrix) - Method in class smile.math.matrix.BigMatrix

Element-wise addition A += B

add(Matrix) - Method in class smile.math.matrix.fp32.Matrix

Element-wise addition A += B

add(Matrix) - Method in class smile.math.matrix.Matrix

Element-wise addition A += B

add(Text) - Method in class smile.nlp.SimpleCorpus

Adds a document to the corpus.

add(Plot) - Method in class smile.plot.swing.Canvas

Add a graphical shape to the canvas.

add(PlotPanel) - Method in class smile.plot.swing.PlotGrid

Add a plot into the frame.

add(Shape) - Method in class smile.plot.swing.Canvas

Add a graphical shape to the canvas.

add(Array2D) - Method in class smile.util.Array2D

A += B.

add(IntArray2D) - Method in class smile.util.IntArray2D

A += B.

add(IntArrayList) - Method in class smile.util.IntArrayList

Appends an array to the end of this list.

add(T) - Method in class smile.sort.HeapSelect

Assimilate a new value from the stream.

Add - Class in smile.data.formula

The term of a + b expression.

Add(Term, Term) - Constructor for class smile.data.formula.Add

Constructor.

add_(double) - Method in class smile.deep.tensor.Tensor

Returns A += b.

add_(float) - Method in class smile.deep.tensor.Tensor

Returns A += b.

add_(Tensor) - Method in class smile.deep.tensor.Tensor

Returns A += B.

add_(Tensor, double) - Method in class smile.deep.tensor.Tensor

Returns A += alpha * B.

add2(double, double, BigMatrix) - Method in class smile.math.matrix.BigMatrix

Element-wise addition A = alpha * A + beta * B^2

add2(double, double, Matrix) - Method in class smile.math.matrix.Matrix

Element-wise addition A = alpha * A + beta * B^2

add2(float, float, Matrix) - Method in class smile.math.matrix.fp32.Matrix

Element-wise addition A = alpha * A + beta * B^2

addAnchor(String) - Method in interface smile.nlp.AnchorText

Adds a link label to the anchor text.

addAnchor(String) - Method in class smile.nlp.SimpleText

addChild(String) - Method in class smile.taxonomy.Concept

Adds a child to this node.

addChild(K[], V, int) - Method in class smile.nlp.Trie.Node

Adds a child.

addChild(Concept) - Method in class smile.taxonomy.Concept

Adds a child to this node.

addDiag(double) - Method in class smile.math.matrix.BigMatrix

A[i, i] += b

addDiag(double) - Method in class smile.math.matrix.Matrix

A[i, i] += b

addDiag(double[]) - Method in class smile.math.matrix.BigMatrix

A[i, i] += b[i]

addDiag(double[]) - Method in class smile.math.matrix.Matrix

A[i, i] += b[i]

addDiag(float) - Method in class smile.math.matrix.fp32.Matrix

A[i, i] += b

addDiag(float[]) - Method in class smile.math.matrix.fp32.Matrix

A[i, i] += b[i]

addEdge(int, int) - Method in class smile.graph.AdjacencyList

addEdge(int, int) - Method in class smile.graph.AdjacencyMatrix

addEdge(int, int) - Method in interface smile.graph.Graph

Creates a new edge in this graph, going from the source vertex to the target vertex, and returns the created edge.

addEdge(int, int, double) - Method in class smile.graph.AdjacencyList

addEdge(int, int, double) - Method in class smile.graph.AdjacencyMatrix

addEdge(int, int, double) - Method in interface smile.graph.Graph

Creates a new edge in this graph, going from the source vertex to the target vertex, and returns the created edge.

addEdge(Neuron) - Method in class smile.vq.hebb.Neuron

Adds an edge.

addEdge(Neuron, int) - Method in class smile.vq.hebb.Neuron

Adds an edge.

addExtension(String) - Method in class smile.swing.FileChooser.SimpleFileFilter

Adds a file type "dot" extension to filter against.

addKeywords(String...) - Method in class smile.taxonomy.Concept

Adds a list of synomym to the concept synset.

addNotify() - Method in class smile.swing.Table.RowHeader

addPropertyChangeListener(PropertyChangeListener) - Method in class smile.plot.swing.Canvas

Add a PropertyChangeListener to the listener list.

AdjacencyList - Class in smile.graph

An adjacency list representation of a graph.

AdjacencyList(int) - Constructor for class smile.graph.AdjacencyList

Constructor.

AdjacencyList(int, boolean) - Constructor for class smile.graph.AdjacencyList

Constructor.

AdjacencyMatrix - Class in smile.graph

An adjacency matrix representation of a graph.

AdjacencyMatrix(int) - Constructor for class smile.graph.AdjacencyMatrix

Constructor.

AdjacencyMatrix(int, boolean) - Constructor for class smile.graph.AdjacencyMatrix

Constructor.

AdjustedMutualInformation - Class in smile.validation.metric

Adjusted Mutual Information (AMI) for comparing clustering.

AdjustedMutualInformation(AdjustedMutualInformation.Method) - Constructor for class smile.validation.metric.AdjustedMutualInformation

Constructor.

AdjustedMutualInformation.Method - Enum Class in smile.validation.metric

The normalization method.

adjustedR2() - Method in class smile.timeseries.AR

Returns adjusted R² statistic.

adjustedR2() - Method in class smile.timeseries.ARMA

Returns adjusted R² statistic.

AdjustedRandIndex - Class in smile.validation.metric

Adjusted Rand Index.

AdjustedRandIndex() - Constructor for class smile.validation.metric.AdjustedRandIndex

adjustedRSquared() - Method in class smile.regression.LinearModel

Returns adjusted R² statistic.

age - Variable in class smile.vq.hebb.Edge

The age of the edges.

age() - Method in class smile.vq.hebb.Neuron

Increments the age of all edges emanating from the neuron.

aggregate(String) - Method in class smile.plot.vega.Field

Sets the aggregation function for the field (e.g., "mean", "sum", "median", "min", "max", "count").

aggregate(String, String, String, String...) - Method in class smile.plot.vega.Transform

Aggregate summarizes a table as one record for each group.

AIC() - Method in class smile.classification.LogisticRegression

Returns the AIC score.

AIC() - Method in class smile.classification.Maxent

Returns the AIC score.

AIC() - Method in class smile.classification.SparseLogisticRegression

Returns the AIC score.

AIC() - Method in class smile.glm.GLM

Returns the AIC score.

AIC(double, int) - Static method in interface smile.validation.ModelSelection

Akaike information criterion.

align(String) - Method in class smile.plot.vega.Concat

align(String) - Method in class smile.plot.vega.Facet

align(String) - Method in class smile.plot.vega.FacetField

Sets the alignment to apply to row/column facet's subplot.

align(String) - Method in class smile.plot.vega.Repeat

align(String) - Method in interface smile.plot.vega.ViewLayoutComposition

Sets the alignment to apply to grid rows and columns.

align(String, String) - Method in class smile.plot.vega.Concat

align(String, String) - Method in class smile.plot.vega.Facet

align(String, String) - Method in class smile.plot.vega.Repeat

align(String, String) - Method in interface smile.plot.vega.ViewLayoutComposition

Sets different alignments for rows and columns.

ALL - Enum constant in enum class smile.math.blas.EigenRange

All eigenvalues will be found.

ALL - Enum constant in enum class smile.math.blas.SVDJob

All left (or right) singular vectors are returned in supplied matrix U (or Vt).

allocate(long) - Static method in class smile.io.Arrow

Creates the root allocator.

allowSpecialTokens(boolean) - Method in class smile.llm.tokenizer.Tiktoken

Sets how special tokens will be encoded.

alpha - Variable in class smile.stat.distribution.BetaDistribution

The shape parameter.

alpha() - Method in class smile.stat.distribution.BetaDistribution

Returns the shape parameter alpha.

AlphaIcon - Class in smile.swing

An Icon wrapper that paints the contained icon with a specified transparency.

AlphaIcon(Icon, float) - Constructor for class smile.swing.AlphaIcon

Creates an AlphaIcon with the specified icon and opacity.

anchor(double) - Method in class smile.plot.vega.BinParams

Sets the value in the binned domain at which to anchor the bins, shifting the bin boundaries if necessary to ensure that a boundary aligns with the anchor value.

AnchorText - Interface in smile.nlp

The anchor text is the visible, clickable text in a hyperlink.

and(Tensor) - Method in class smile.deep.tensor.Tensor

Returns logical AND of two boolean tensors.

and(Predicate...) - Static method in class smile.plot.vega.Predicate

Logical AND composition to combine predicates.

and_(Tensor) - Method in class smile.deep.tensor.Tensor

Returns logical AND of two boolean tensors.

andThen(Transform) - Method in interface smile.data.transform.Transform

Returns a composed function that first applies this function to its input, and then applies the after function to the result.

antecedent - Variable in class smile.association.AssociationRule

Antecedent itemset.

anyNull() - Method in interface smile.data.Tuple

Returns true if there are any NULL values in this tuple.

anyNull() - Method in interface smile.data.vector.Vector

Returns true if there are any NULL values in this row.

append(int, double) - Method in class smile.util.SparseArray

Append an entry to the array, optimizing for the case where the index is greater than all existing indices in the array.

apply(double) - Method in interface smile.math.Function

Computes the value of the function at x.

apply(double) - Method in interface smile.math.kernel.DotProductKernel

Computes the kernel function.

apply(double) - Method in interface smile.math.kernel.IsotropicKernel

Computes the kernel function.

apply(double[]) - Method in class smile.feature.extraction.KernelPCA

apply(double[]) - Method in class smile.feature.extraction.Projection

Project a data point to the feature space.

apply(double...) - Method in interface smile.math.MultivariateFunction

Computes the value of the function at x.

apply(double[][]) - Method in class smile.feature.extraction.Projection

Project a set of data to the feature space.

apply(double, FPTree) - Static method in class smile.association.ARM

Mines the association rules.

apply(int) - Method in interface smile.data.DataFrame

Returns the row at the specified index.

apply(int) - Method in interface smile.data.Dataset

Returns the index at the specified index.

apply(int) - Method in interface smile.data.Tuple

Returns the value at position i.

apply(int) - Method in interface smile.data.vector.BaseVector

Returns the value at position i, which may be null.

apply(int) - Method in class smile.math.Complex.Array

Returns the i-th element.

apply(int) - Method in interface smile.math.IntFunction

Computes the value of the function at x.

apply(int) - Method in interface smile.math.TimeFunction

Returns the function value at time step t.

apply(int...) - Method in interface smile.data.vector.BaseVector

Returns a new vector with selected entries.

apply(int, int) - Method in class smile.math.matrix.fp32.IMatrix

Returns A[i,j].

apply(int, int) - Method in class smile.math.matrix.IMatrix

Returns A[i,j] for Scala users.

apply(int, int) - Method in class smile.util.Array2D

Returns A[i, j].

apply(int, int) - Method in class smile.util.IntArray2D

Returns A[i, j].

apply(int, int, int, Fitness<BitString>) - Method in class smile.feature.selection.GAFE

Genetic algorithm based feature selection for classification.

apply(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

apply(String) - Method in interface smile.data.DataFrame

Selects column based on the column name and return it as a Column.

apply(String) - Method in interface smile.data.Tuple

Returns the value by field name.

apply(String) - Method in class smile.feature.extraction.BagOfWords

Returns the bag-of-words features of a document.

apply(String) - Method in class smile.feature.extraction.HashEncoder

Returns the bag-of-words features of a document.

apply(String) - Method in class smile.nlp.embedding.Word2Vec

Returns the embedding vector of a word.

apply(String) - Method in interface smile.nlp.tokenizer.Tokenizer

apply(JTable) - Method in class smile.swing.table.TableColumnSettings

Apply this column settings to given table.

apply(JTable) - Static method in class smile.swing.table.TableCopyPasteAdapter

apply(FPTree) - Static method in class smile.association.FPGrowth

Mines the frequent item sets.

apply(DataFrame) - Method in interface smile.data.formula.Feature

Applies the term on a data frame.

apply(DataFrame) - Method in class smile.data.transform.ColumnTransform

apply(DataFrame) - Method in interface smile.data.transform.Transform

Applies this transform to the given argument.

apply(DataFrame) - Method in class smile.feature.extraction.BinaryEncoder

Generates the compact representation of sparse binary features for a data frame.

apply(DataFrame) - Method in class smile.feature.extraction.Projection

apply(DataFrame) - Method in class smile.feature.extraction.SparseEncoder

Generates the sparse representation of a data frame.

apply(DataFrame) - Method in class smile.feature.imputation.SimpleImputer

apply(Tuple) - Method in interface smile.data.formula.Feature

Applies the term on a tuple.

apply(Tuple) - Method in class smile.data.formula.Formula

Apply the formula on a tuple to generate the model data.

apply(Tuple) - Method in class smile.data.transform.ColumnTransform

apply(Tuple) - Method in class smile.feature.extraction.BagOfWords

apply(Tuple) - Method in class smile.feature.extraction.BinaryEncoder

Generates the compact representation of sparse binary features for given object.

apply(Tuple) - Method in class smile.feature.extraction.Projection

apply(Tuple) - Method in class smile.feature.extraction.SparseEncoder

Generates the sparse representation of given object.

apply(Tuple) - Method in class smile.feature.imputation.KMedoidsImputer

apply(Tuple) - Method in class smile.feature.imputation.KNNImputer

apply(Tuple) - Method in class smile.feature.imputation.SimpleImputer

apply(Tuple) - Method in class smile.feature.transform.Normalizer

apply(Tensor) - Method in interface smile.deep.layer.Layer

apply(Tensor) - Method in class smile.deep.Model

apply(BitString, BitString) - Method in enum class smile.gap.Crossover

Returns a pair of offsprings by crossovering parent chromosomes.

apply(T) - Method in class smile.manifold.KPCA

apply(T[]) - Method in interface smile.gap.Selection

Select a chromosome with replacement from the population based on their fitness.

apply(T[]) - Method in class smile.manifold.KPCA

Project a set of data to the feature space.

apply(T, T) - Method in interface smile.math.distance.Distance

Returns the distance measure between two objects.

apply(T, T) - Method in interface smile.math.kernel.MercerKernel

Kernel function.

applyAsBoolean(Tuple) - Method in interface smile.data.formula.Feature

Applies the term on a data object and produces an boolean-valued result.

applyAsByte(Tuple) - Method in interface smile.data.formula.Feature

Applies the term on a data object and produces an byte-valued result.

applyAsChar(Tuple) - Method in interface smile.data.formula.Feature

Applies the term on a data object and produces an char-valued result.

applyAsDouble(double[]) - Method in interface smile.math.MultivariateFunction

applyAsDouble(Tuple) - Method in interface smile.data.formula.Feature

Applies the term on a data object and produces an double-valued result.

applyAsDouble(T) - Method in interface smile.classification.Classifier

applyAsDouble(T) - Method in interface smile.regression.Regression

applyAsDouble(T, T) - Method in interface smile.math.distance.Distance

applyAsDouble(T, T) - Method in interface smile.math.kernel.MercerKernel

applyAsFloat(Tuple) - Method in interface smile.data.formula.Feature

Applies the term on a data object and produces an float-valued result.

applyAsFloat(T) - Method in interface smile.util.ToFloatFunction

Applies this function to the given argument.

applyAsInt(Tuple) - Method in interface smile.data.formula.Feature

Applies the term on a data object and produces an int-valued result.

applyAsInt(T) - Method in interface smile.classification.Classifier

applyAsLong(Tuple) - Method in interface smile.data.formula.Feature

Applies the term on a data object and produces an long-valued result.

applyAsShort(Tuple) - Method in interface smile.data.formula.Feature

Applies the term on a data object and produces an short-valued result.

ar() - Method in class smile.timeseries.AR

Returns the linear coefficients of AR (without intercept).

ar() - Method in class smile.timeseries.ARMA

Returns the linear coefficients of AR(p).

AR - Class in smile.timeseries

Autoregressive model.

AR(double[], double[], double, AR.Method) - Constructor for class smile.timeseries.AR

Constructor.

AR.Method - Enum Class in smile.timeseries

The fitting method.

arange(double, double, double) - Static method in class smile.deep.tensor.Tensor

Returns a 1-D tensor of size (end - start) / step with values from the interval [start, end) taken with common difference step beginning from start.

arange(float, float, float) - Static method in class smile.deep.tensor.Tensor

Returns a 1-D tensor of size (end - start) / step with values from the interval [start, end) taken with common difference step beginning from start.

arange(int, int, int) - Static method in class smile.deep.tensor.Tensor

Returns a 1-D tensor of size (end - start) / step with values from the interval [start, end) taken with common difference step beginning from start.

arange(long, long, long) - Static method in class smile.deep.tensor.Tensor

Returns a 1-D tensor of size (end - start) / step with values from the interval [start, end) taken with common difference step beginning from start.

arff(String) - Static method in interface smile.io.Read

Reads an ARFF file.

arff(Path) - Static method in interface smile.io.Read

Reads an ARFF file.

arff(DataFrame, Path, String) - Static method in interface smile.io.Write

Writes the data frame to an ARFF file.

Arff - Class in smile.io

Weka ARFF (attribute relation file format) is an ASCII text file format that is essentially a CSV file with a header that describes the meta-data.

Arff(Reader) - Constructor for class smile.io.Arff

Constructor.

Arff(String) - Constructor for class smile.io.Arff

Constructor.

Arff(String, Charset) - Constructor for class smile.io.Arff

Constructor.

Arff(Path) - Constructor for class smile.io.Arff

Constructor.

Arff(Path, Charset) - Constructor for class smile.io.Arff

Constructor.

argmax(int, boolean) - Method in class smile.deep.tensor.Tensor

Returns the indices of the maximum value of a tensor across a dimension.

aria(boolean) - Method in class smile.plot.vega.Axis

Sets if ARIA attributes should be included (SVG output only).

aria(boolean) - Method in class smile.plot.vega.Legend

Sets if ARIA attributes should be included (SVG output only).

aria(boolean) - Method in class smile.plot.vega.Mark

Sets the aria.

ARM - Class in smile.association

Association Rule Mining.

ARMA - Class in smile.timeseries

Autoregressive moving-average model.

ARMA(double[], double[], double[], double, double[], double[]) - Constructor for class smile.timeseries.ARMA

Constructor.

ARPACK - Class in smile.math.matrix

ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems.

ARPACK - Class in smile.math.matrix.fp32

ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems.

ARPACK.AsymmOption - Enum Class in smile.math.matrix

Which eigenvalues of asymmetric matrix to compute.

ARPACK.AsymmOption - Enum Class in smile.math.matrix.fp32

Which eigenvalues of asymmetric matrix to compute.

ARPACK.SymmOption - Enum Class in smile.math.matrix

Which eigenvalues of symmetric matrix to compute.

ARPACK.SymmOption - Enum Class in smile.math.matrix.fp32

Which eigenvalues of symmetric matrix to compute.

array() - Method in interface smile.data.vector.BaseVector

Returns the array that backs this vector.

array() - Method in interface smile.data.vector.BooleanVector

array() - Method in interface smile.data.vector.ByteVector

array() - Method in interface smile.data.vector.CharVector

array() - Method in interface smile.data.vector.DoubleVector

array() - Method in interface smile.data.vector.FloatVector

array() - Method in interface smile.data.vector.IntVector

array() - Method in interface smile.data.vector.LongVector

array() - Method in interface smile.data.vector.ShortVector

array() - Method in record class smile.util.Bytes

Returns the value of the array record component.

array(DataType) - Static method in class smile.data.type.DataTypes

Creates an array data type.

Array - Enum constant in enum class smile.data.type.DataType.ID

Array type ID.

Array(int) - Constructor for class smile.math.Complex.Array

Constructor.

Array2D - Class in smile.util

2-dimensional array of doubles.

Array2D(double[][]) - Constructor for class smile.util.Array2D

Constructor.

Array2D(int, int) - Constructor for class smile.util.Array2D

Constructor of all-zero matrix.

Array2D(int, int, double) - Constructor for class smile.util.Array2D

Constructor.

Array2D(int, int, double[]) - Constructor for class smile.util.Array2D

Constructor.

ArrayType - Class in smile.data.type

Array of primitive data type.

arrow(String) - Static method in interface smile.io.Read

Reads an Apache Arrow file.

arrow(Path) - Static method in interface smile.io.Read

Reads an Apache Arrow file.

arrow(DataFrame, Path) - Static method in interface smile.io.Write

Writes an Apache Arrow file.

Arrow - Class in smile.io

Apache Arrow is a cross-language development platform for in-memory data.

Arrow() - Constructor for class smile.io.Arrow

Constructor.

Arrow(int) - Constructor for class smile.io.Arrow

Constructor.

as() - Method in record class smile.plot.vega.WindowTransformField

Returns the value of the as record component.

as(String...) - Method in class smile.plot.vega.DensityTransform

Sets the output fields for the sample value and corresponding density estimate.

as(String...) - Method in class smile.plot.vega.LoessTransform

Sets the output field names for the smoothed points generated by the loess transform.

as(String...) - Method in class smile.plot.vega.QuantileTransform

Sets the output field names for the probability and quantile values.

as(String...) - Method in class smile.plot.vega.RegressionTransform

Sets the output field names for the smoothed points generated by the loess transform.

asin() - Method in class smile.deep.tensor.Tensor

Returns a new tensor with the arcsine of the elements of input.

asin(String) - Static method in interface smile.data.formula.Terms

The asin(x) term.

asin(Term) - Static method in interface smile.data.formula.Terms

The asin(x) term.

asin_() - Method in class smile.deep.tensor.Tensor

Computes the arcsine of the elements of input in place.

asolve(double[], double[]) - Method in interface smile.math.matrix.IMatrix.Preconditioner

Solve P * x = b for the preconditioner matrix P.

asolve(float[], float[]) - Method in interface smile.math.matrix.fp32.IMatrix.Preconditioner

Solve P * x = b for the preconditioner matrix P.

AssociationRule - Class in smile.association

Association rule object.

AssociationRule(int[], int[], double, double, double, double) - Constructor for class smile.association.AssociationRule

Constructor.

asTorch() - Method in class smile.deep.activation.ActivationFunction

asTorch() - Method in class smile.deep.layer.AdaptiveAvgPool2dLayer

asTorch() - Method in class smile.deep.layer.AvgPool2dLayer

asTorch() - Method in class smile.deep.layer.BatchNorm1dLayer

asTorch() - Method in class smile.deep.layer.BatchNorm2dLayer

asTorch() - Method in class smile.deep.layer.Conv2dLayer

asTorch() - Method in class smile.deep.layer.DropoutLayer

asTorch() - Method in class smile.deep.layer.EmbeddingLayer

asTorch() - Method in class smile.deep.layer.FullyConnectedLayer

asTorch() - Method in class smile.deep.layer.GroupNormLayer

asTorch() - Method in interface smile.deep.layer.Layer

Returns the PyTorch Module object.

asTorch() - Method in class smile.deep.layer.LayerBlock

asTorch() - Method in class smile.deep.layer.MaxPool2dLayer

asTorch() - Method in class smile.deep.Model

Returns the PyTorch Module object.

asTorch() - Method in class smile.deep.tensor.Device

Returns the PyTorch device object.

asTorch() - Method in class smile.deep.tensor.Tensor

Returns the PyTorch tensor object.

asTorch() - Method in class smile.llm.PositionalEncoding

asTorch() - Method in class smile.vision.layer.StochasticDepth

asum(double[]) - Method in interface smile.math.blas.BLAS

Sums the absolute values of the elements of a vector.

asum(float[]) - Method in interface smile.math.blas.BLAS

Sums the absolute values of the elements of a vector.

asum(int, double[], int) - Method in interface smile.math.blas.BLAS

Sums the absolute values of the elements of a vector.

asum(int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

asum(int, float[], int) - Method in interface smile.math.blas.BLAS

Sums the absolute values of the elements of a vector.

asum(int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

ata() - Method in class smile.math.matrix.BigMatrix

Returns A' * A.

ata() - Method in class smile.math.matrix.fp32.Matrix

Returns A' * A.

ata() - Method in class smile.math.matrix.fp32.SparseMatrix

Returns A' * A.

ata() - Method in class smile.math.matrix.Matrix

Returns A' * A.

ata() - Method in class smile.math.matrix.SparseMatrix

Returns A' * A.

atan(String) - Static method in interface smile.data.formula.Terms

The atan(x) term.

atan(Term) - Static method in interface smile.data.formula.Terms

The atan(x) term.

attach(AutoCloseable...) - Method in class smile.util.AutoScope

Attaches resources to this Scope.

attractors - Variable in class smile.clustering.DENCLUE

The density attractor of each observation.

auc - Variable in class smile.validation.ClassificationMetrics

The AUC on validation data.

AUC - Class in smile.validation.metric

The area under the curve (AUC).

AUC() - Constructor for class smile.validation.metric.AUC

AutoScope - Class in smile.util

AutoScope allows for predictable, deterministic resource deallocation.

AutoScope(AutoCloseable...) - Constructor for class smile.util.AutoScope

Constructors.

autosize() - Method in class smile.plot.vega.Concat

autosize() - Method in class smile.plot.vega.Config

Sets the overall size of the visualization.

autosize() - Method in class smile.plot.vega.Facet

autosize() - Method in class smile.plot.vega.Repeat

autosize() - Method in class smile.plot.vega.VegaLite

Sets the overall size of the visualization.

autosize() - Method in class smile.plot.vega.View

autosize(String, boolean, String) - Method in class smile.plot.vega.Concat

autosize(String, boolean, String) - Method in class smile.plot.vega.Config

Sets the overall size of the visualization.

autosize(String, boolean, String) - Method in class smile.plot.vega.Facet

autosize(String, boolean, String) - Method in class smile.plot.vega.Repeat

autosize(String, boolean, String) - Method in class smile.plot.vega.VegaLite

Sets the overall size of the visualization.

autosize(String, boolean, String) - Method in class smile.plot.vega.View

Averaging - Enum Class in smile.deep.metric

The averaging strategy to aggregate binary performance metrics across multi-classes.

avg - Variable in class smile.validation.ClassificationValidations

The average of metrics.

avg - Variable in class smile.validation.RegressionValidations

The average of metrics.

avgDocSize() - Method in interface smile.nlp.Corpus

Returns the average size of documents in the corpus.

avgDocSize() - Method in class smile.nlp.SimpleCorpus

avgPool2d(int) - Static method in interface smile.deep.layer.Layer

Returns an average pooling layer that reduces a tensor by combining cells, and assigning the average value of the input cells to the output cell.

AvgPool2dLayer - Class in smile.deep.layer

An average pooling layer that reduces a tensor by combining cells, and assigning the average value of the input cells to the output cell.

AvgPool2dLayer(int) - Constructor for class smile.deep.layer.AvgPool2dLayer

Constructor.

AvgPool2dLayer(int, int) - Constructor for class smile.deep.layer.AvgPool2dLayer

Constructor.

avro(String, InputStream) - Static method in interface smile.io.Read

Reads an Apache Avro file.

avro(String, String) - Static method in interface smile.io.Read

Reads an Apache Avro file.

avro(Path, InputStream) - Static method in interface smile.io.Read

Reads an Apache Avro file.

avro(Path, Path) - Static method in interface smile.io.Read

Reads an Apache Avro file.

Avro - Class in smile.io

Apache Avro is a data serialization system.

Avro(InputStream) - Constructor for class smile.io.Avro

Constructor.

Avro(Path) - Constructor for class smile.io.Avro

Constructor.

Avro(Schema) - Constructor for class smile.io.Avro

Constructor.

axis() - Method in class smile.plot.vega.Config

Returns the axis definition object.

axis() - Method in class smile.plot.vega.Field

Returns the axis definition object.

axis() - Method in class smile.plot.vega.ViewConfig

Returns the axis definition object.

Axis - Class in smile.plot.swing

This class describes an axis of a coordinate system.

Axis - Class in smile.plot.vega

Axes provide axis lines, ticks, and labels to convey how a positional range represents a data range.

Axis(Base, int) - Constructor for class smile.plot.swing.Axis

Constructor.

axpy(double, double[], double[]) - Method in interface smile.math.blas.BLAS

Computes a constant alpha times a vector x plus a vector y.

axpy(double, double[], double[]) - Static method in class smile.math.MathEx

Update an array by adding a multiple of another array y = a * x + y.

axpy(float, float[], float[]) - Method in interface smile.math.blas.BLAS

Computes a constant alpha times a vector x plus a vector y.

axpy(int, double, double[], int, double[], int) - Method in interface smile.math.blas.BLAS

Computes a constant alpha times a vector x plus a vector y.

axpy(int, double, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

axpy(int, float, float[], int, float[], int) - Method in interface smile.math.blas.BLAS

Computes a constant alpha times a vector x plus a vector y.

axpy(int, float, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

B

b - Variable in class smile.validation.metric.ContingencyTable

The column sum of contingency table.

B - Variable in class smile.vq.BIRCH

The branching factor of non-leaf nodes.

background() - Method in class smile.plot.vega.View

Returns the view background's fill and stroke object.

background(String) - Method in class smile.plot.vega.Concat

background(String) - Method in class smile.plot.vega.Config

Sets the background with CSS color property.

background(String) - Method in class smile.plot.vega.Facet

background(String) - Method in class smile.plot.vega.Repeat

background(String) - Method in class smile.plot.vega.VegaLite

Sets the background of the entire view with CSS color property.

background(String) - Method in class smile.plot.vega.View

Background - Class in smile.plot.vega

The view background of a single-view or layer specification.

backpopagateDropout() - Method in class smile.base.mlp.Layer

Propagates the errors back through the (implicit) dropout layer.

backpropagate(boolean) - Method in class smile.base.mlp.MultilayerPerceptron

Propagates the errors back through the network.

backpropagate(double[]) - Method in class smile.base.mlp.HiddenLayer

backpropagate(double[]) - Method in class smile.base.mlp.InputLayer

backpropagate(double[]) - Method in class smile.base.mlp.Layer

Propagates the errors back to a lower layer.

backpropagate(double[]) - Method in class smile.base.mlp.OutputLayer

backward() - Method in class smile.deep.tensor.Tensor

Computes the gradients.

Bag - Class in smile.validation

A bag of random selected samples.

Bag(int[], int[]) - Constructor for class smile.validation.Bag

Constructor.

BagOfWords - Class in smile.feature.extraction

The bag-of-words feature of text used in natural language processing and information retrieval.

BagOfWords(String[], Function<String, String[]>, String[], boolean) - Constructor for class smile.feature.extraction.BagOfWords

Constructor.

BagOfWords(Function<String, String[]>, String[]) - Constructor for class smile.feature.extraction.BagOfWords

Constructor.

BandMatrix - Class in smile.math.matrix

A band matrix is a sparse matrix, whose non-zero entries are confined to a diagonal band, comprising the main diagonal and zero or more diagonals on either side.

BandMatrix - Class in smile.math.matrix.fp32

A band matrix is a sparse matrix, whose non-zero entries are confined to a diagonal band, comprising the main diagonal and zero or more diagonals on either side.

BandMatrix(int, int, int, int) - Constructor for class smile.math.matrix.BandMatrix

Constructor.

BandMatrix(int, int, int, int) - Constructor for class smile.math.matrix.fp32.BandMatrix

Constructor.

BandMatrix(int, int, int, int, double[][]) - Constructor for class smile.math.matrix.BandMatrix

Constructor.

BandMatrix(int, int, int, int, float[][]) - Constructor for class smile.math.matrix.fp32.BandMatrix

Constructor.

BandMatrix.Cholesky - Class in smile.math.matrix

The Cholesky decomposition of a symmetric, positive-definite matrix.

BandMatrix.Cholesky - Class in smile.math.matrix.fp32

The Cholesky decomposition of a symmetric, positive-definite matrix.

BandMatrix.LU - Class in smile.math.matrix

The LU decomposition.

BandMatrix.LU - Class in smile.math.matrix.fp32

The LU decomposition.

bandPosition(double) - Method in class smile.plot.vega.Axis

For band scales, sets the interpolation fraction where axis ticks should be positioned.

bandwidth() - Method in class smile.stat.distribution.KernelDensity

Returns the bandwidth of kernel.

bandwidth(double) - Method in class smile.plot.vega.DensityTransform

Sets the bandwidth (standard deviation) of the Gaussian kernel.

bandwidth(double) - Method in class smile.plot.vega.LoessTransform

Sets a bandwidth parameter in the range [0, 1] that determines the amount of smoothing.

Bar - Class in smile.plot.swing

Bars with heights proportional to the value.

Bar(double[][], double, Color) - Constructor for class smile.plot.swing.Bar

Constructor.

BarPlot - Class in smile.plot.swing

A barplot draws bars with heights proportional to the value.

BarPlot(Bar...) - Constructor for class smile.plot.swing.BarPlot

Constructor.

BarPlot(Bar[], Legend[]) - Constructor for class smile.plot.swing.BarPlot

Constructor.

base(int) - Method in class smile.plot.vega.BinParams

Sets the number base to use for automatic bin determination (default is base 10).

Base - Class in smile.plot.swing

The coordinate base of PlotCanvas.

Base(double[], double[]) - Constructor for class smile.plot.swing.Base

Constructor.

Base(double[], double[], boolean) - Constructor for class smile.plot.swing.Base

Constructor.

BaseVector<T,TS,S> - Interface in smile.data.vector

Base interface for immutable named vectors, which are sequences of elements supporting random access and sequential stream operations.

batch(int) - Method in interface smile.data.Dataset

Returns an iterator of mini-batches.

batchNorm1d(int) - Static method in interface smile.deep.layer.Layer

Returns a normalization layer that re-centers and normalizes the output of one layer before feeding it to another.

batchNorm1d(int, double, double, boolean) - Static method in interface smile.deep.layer.Layer

Returns a normalization layer that re-centers and normalizes the output of one layer before feeding it to another.

BatchNorm1dLayer - Class in smile.deep.layer

A batch normalization layer that re-centers and normalizes the output of one layer before feeding it to another.

BatchNorm1dLayer(int) - Constructor for class smile.deep.layer.BatchNorm1dLayer

Constructor.

BatchNorm1dLayer(int, double, double, boolean) - Constructor for class smile.deep.layer.BatchNorm1dLayer

Constructor.

batchNorm2d(int) - Static method in interface smile.deep.layer.Layer

Returns a normalization layer that re-centers and normalizes the output of one layer before feeding it to another.

batchNorm2d(int, double, double, boolean) - Static method in interface smile.deep.layer.Layer

Returns a normalization layer that re-centers and normalizes the output of one layer before feeding it to another.

BatchNorm2dLayer - Class in smile.deep.layer

A batch normalization layer that re-centers and normalizes the output of one layer before feeding it to another.

BatchNorm2dLayer(int) - Constructor for class smile.deep.layer.BatchNorm2dLayer

Constructor.

BatchNorm2dLayer(int, double, double, boolean) - Constructor for class smile.deep.layer.BatchNorm2dLayer

Constructor.

BBDTree - Class in smile.clustering

Balanced Box-Decomposition Tree.

BBDTree(double[][]) - Constructor for class smile.clustering.BBDTree

Constructs a tree out of the given n data points living in R^d.

BE - Enum constant in enum class smile.math.matrix.ARPACK.SymmOption

Computes nev eigenvalues, half from each end of the spectrum.

BE - Enum constant in enum class smile.math.matrix.fp32.ARPACK.SymmOption

Computes nev eigenvalues, half from each end of the spectrum.

Bernoulli - Interface in smile.glm.model

The response variable is of Bernoulli distribution.

BERNOULLI - Enum constant in enum class smile.classification.DiscreteNaiveBayes.Model

The document Bernoulli model generates an indicator for each term of the vocabulary, either indicating presence of the term in the document or indicating absence.

bernoulli_(double) - Method in class smile.deep.tensor.Tensor

Draws binary random numbers (0 or 1) from a Bernoulli distribution.

BernoulliDistribution - Class in smile.stat.distribution

Bernoulli distribution is a discrete probability distribution, which takes value 1 with success probability p and value 0 with failure probability q = 1 - p.

BernoulliDistribution(boolean[]) - Constructor for class smile.stat.distribution.BernoulliDistribution

Construct an Bernoulli from the given samples.

BernoulliDistribution(double) - Constructor for class smile.stat.distribution.BernoulliDistribution

Constructor.

BERT - Class in smile.llm

Bidirectional Encoder Representations from Transformers (BERT).

BERT() - Constructor for class smile.llm.BERT

BestLocalizedWavelet - Class in smile.wavelet

Best localized wavelets.

BestLocalizedWavelet(int) - Constructor for class smile.wavelet.BestLocalizedWavelet

Constructor.

beta - Variable in class smile.glm.GLM

The linear weights.

beta - Variable in class smile.stat.distribution.BetaDistribution

The shape parameter.

beta() - Method in class smile.stat.distribution.BetaDistribution

Returns the shape parameter beta.

beta(double, double) - Static method in class smile.math.special.Beta

Beta function, also called the Euler integral of the first kind.

Beta - Class in smile.math.special

The beta function, also called the Euler integral of the first kind.

BetaDistribution - Class in smile.stat.distribution

The beta distribution is defined on the interval [0, 1] parameterized by two positive shape parameters, typically denoted by α and β.

BetaDistribution(double, double) - Constructor for class smile.stat.distribution.BetaDistribution

Constructor.

BFGS - Class in smile.math

The Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization problems.

BFGS() - Constructor for class smile.math.BFGS

BFloat16 - Enum constant in enum class smile.deep.tensor.ScalarType

The bfloat16 (brain floating point) floating-point format occupies 16 bits.

bfs() - Method in class smile.graph.AdjacencyList

bfs() - Method in class smile.graph.AdjacencyMatrix

bfs() - Method in interface smile.graph.Graph

Breadth-first search connected components of graph.

bfs(Visitor) - Method in class smile.graph.AdjacencyList

bfs(Visitor) - Method in class smile.graph.AdjacencyMatrix

bfs(Visitor) - Method in interface smile.graph.Graph

BFS search on graph and performs some operation defined in visitor on each vertex during traveling.

bias - Variable in class smile.base.mlp.Layer

The bias.

biasGradient - Variable in class smile.base.mlp.Layer

The bias gradient.

biasGradientMoment1 - Variable in class smile.base.mlp.Layer

The first moment of bias gradient.

biasGradientMoment2 - Variable in class smile.base.mlp.Layer

The second moment of bias gradient.

biasUpdate - Variable in class smile.base.mlp.Layer

The bias update.

bic - Variable in class smile.stat.distribution.DiscreteExponentialFamilyMixture

The BIC score when the distribution is fit on a sample data.

bic - Variable in class smile.stat.distribution.ExponentialFamilyMixture

The BIC score when the distribution is fit on a sample data.

bic - Variable in class smile.stat.distribution.MultivariateExponentialFamilyMixture

The BIC score when the distribution is fit on a sample data.

bic(double[]) - Method in class smile.stat.distribution.DiscreteMixture

Returns the BIC score.

bic(double[]) - Method in class smile.stat.distribution.Mixture

Returns the BIC score.

bic(double[][]) - Method in class smile.stat.distribution.MultivariateMixture

Returns the BIC score.

BIC() - Method in class smile.glm.GLM

Returns the BIC score.

BIC(double, int, int) - Static method in interface smile.validation.ModelSelection

Bayesian information criterion.

BicubicInterpolation - Class in smile.interpolation

Bicubic interpolation in a two-dimensional regular grid.

BicubicInterpolation(double[], double[], double[][]) - Constructor for class smile.interpolation.BicubicInterpolation

Constructor.

BigMatrix - Class in smile.math.matrix

Big dense matrix of double precision values for more than 2 billion elements.

BigMatrix(int, int) - Constructor for class smile.math.matrix.BigMatrix

Constructor of zero matrix.

BigMatrix(int, int, double) - Constructor for class smile.math.matrix.BigMatrix

Constructor.

BigMatrix(int, int, int, DoublePointer) - Constructor for class smile.math.matrix.BigMatrix

Constructor.

BigMatrix.Cholesky - Class in smile.math.matrix

The Cholesky decomposition of a symmetric, positive-definite matrix.

BigMatrix.EVD - Class in smile.math.matrix

Eigenvalue decomposition.

BigMatrix.LU - Class in smile.math.matrix

The LU decomposition.

BigMatrix.QR - Class in smile.math.matrix

The QR decomposition.

BigMatrix.SVD - Class in smile.math.matrix

Singular Value Decomposition.

Bigram - Class in smile.nlp

Bigrams or digrams are groups of two words, and are very commonly used as the basis for simple statistical analysis of text.

Bigram - Class in smile.nlp.collocation

Collocations are expressions of multiple words which commonly co-occur.

Bigram(String, String) - Constructor for class smile.nlp.Bigram

Constructor.

Bigram(String, String, int, double) - Constructor for class smile.nlp.collocation.Bigram

Constructor.

bigrams() - Method in interface smile.nlp.Corpus

Returns the iterator over the bigrams in the corpus.

bigrams() - Method in class smile.nlp.SimpleCorpus

BilinearInterpolation - Class in smile.interpolation

Bilinear interpolation in a two-dimensional regular grid.

BilinearInterpolation(double[], double[], double[][]) - Constructor for class smile.interpolation.BilinearInterpolation

Constructor.

bin(boolean) - Method in class smile.plot.vega.FacetField

Turns on/off binning a quantitative field.

bin(boolean) - Method in class smile.plot.vega.Field

Turns on/off binning a quantitative field.

bin(String) - Method in class smile.plot.vega.FacetField

Indicates that the data for x or y channel are binned before they are imported into Vega-Lite.

bin(String) - Method in class smile.plot.vega.Field

Indicates that the data for x or y channel are binned before they are imported into Vega-Lite.

bin(String, String) - Method in class smile.plot.vega.Transform

Adds a bin transformation.

bin(BinParams) - Method in class smile.plot.vega.Field

Sets custom binning parameters.

binary(int, KernelMachine<int[]>) - Static method in class smile.base.svm.LinearKernelMachine

Creates a linear kernel machine.

binary(String) - Static method in interface smile.math.kernel.MercerKernel

Returns a binary sparse kernel function.

BinaryEncoder - Class in smile.feature.extraction

Encodes categorical features using sparse one-hot scheme.

BinaryEncoder(StructType, String...) - Constructor for class smile.feature.extraction.BinaryEncoder

Constructor.

BinarySparseDataset<T> - Interface in smile.data

Binary sparse dataset.

BinarySparseGaussianKernel - Class in smile.math.kernel

Gaussian kernel, also referred as RBF kernel or squared exponential kernel.

BinarySparseGaussianKernel(double) - Constructor for class smile.math.kernel.BinarySparseGaussianKernel

Constructor.

BinarySparseGaussianKernel(double, double, double) - Constructor for class smile.math.kernel.BinarySparseGaussianKernel

Constructor.

BinarySparseHyperbolicTangentKernel - Class in smile.math.kernel

The hyperbolic tangent kernel on binary sparse data.

BinarySparseHyperbolicTangentKernel() - Constructor for class smile.math.kernel.BinarySparseHyperbolicTangentKernel

Constructor with scale 1.0 and offset 0.0.

BinarySparseHyperbolicTangentKernel(double, double) - Constructor for class smile.math.kernel.BinarySparseHyperbolicTangentKernel

Constructor.

BinarySparseHyperbolicTangentKernel(double, double, double[], double[]) - Constructor for class smile.math.kernel.BinarySparseHyperbolicTangentKernel

Constructor.

BinarySparseLaplacianKernel - Class in smile.math.kernel

Laplacian kernel, also referred as exponential kernel.

BinarySparseLaplacianKernel(double) - Constructor for class smile.math.kernel.BinarySparseLaplacianKernel

Constructor.

BinarySparseLaplacianKernel(double, double, double) - Constructor for class smile.math.kernel.BinarySparseLaplacianKernel

Constructor.

BinarySparseLinearKernel - Class in smile.math.kernel

The linear dot product kernel on sparse binary arrays in int[], which are the indices of nonzero elements.

BinarySparseLinearKernel() - Constructor for class smile.math.kernel.BinarySparseLinearKernel

Constructor.

BinarySparseMaternKernel - Class in smile.math.kernel

The class of Matérn kernels is a generalization of the Gaussian/RBF.

BinarySparseMaternKernel(double, double) - Constructor for class smile.math.kernel.BinarySparseMaternKernel

Constructor.

BinarySparseMaternKernel(double, double, double, double) - Constructor for class smile.math.kernel.BinarySparseMaternKernel

Constructor.

BinarySparsePolynomialKernel - Class in smile.math.kernel

The polynomial kernel on binary sparse data.

BinarySparsePolynomialKernel(int) - Constructor for class smile.math.kernel.BinarySparsePolynomialKernel

Constructor with scale 1 and offset 0.

BinarySparsePolynomialKernel(int, double, double) - Constructor for class smile.math.kernel.BinarySparsePolynomialKernel

Constructor.

BinarySparsePolynomialKernel(int, double, double, double[], double[]) - Constructor for class smile.math.kernel.BinarySparsePolynomialKernel

Constructor.

BinarySparseThinPlateSplineKernel - Class in smile.math.kernel

The Thin Plate Spline kernel on binary sparse data.

BinarySparseThinPlateSplineKernel(double) - Constructor for class smile.math.kernel.BinarySparseThinPlateSplineKernel

Constructor.

BinarySparseThinPlateSplineKernel(double, double, double) - Constructor for class smile.math.kernel.BinarySparseThinPlateSplineKernel

Constructor.

bind(StructType) - Method in class smile.data.formula.Abs

bind(StructType) - Method in class smile.data.formula.Add

bind(StructType) - Method in class smile.data.formula.Date

bind(StructType) - Method in class smile.data.formula.Div

bind(StructType) - Method in class smile.data.formula.DoubleFunction

bind(StructType) - Method in class smile.data.formula.FactorCrossing

bind(StructType) - Method in class smile.data.formula.FactorInteraction

bind(StructType) - Method in class smile.data.formula.Formula

Binds the formula to a schema and returns the schema of predictors.

bind(StructType) - Method in class smile.data.formula.IntFunction

bind(StructType) - Method in class smile.data.formula.Mul

bind(StructType) - Method in class smile.data.formula.Sub

bind(StructType) - Method in interface smile.data.formula.Term

Binds the term to a schema.

binomial(double[][], int[]) - Static method in class smile.classification.LogisticRegression

Fits binomial logistic regression.

binomial(double[][], int[], double, double, int) - Static method in class smile.classification.LogisticRegression

Fits binomial logistic regression.

binomial(double[][], int[], Properties) - Static method in class smile.classification.LogisticRegression

Fits binomial logistic regression.

binomial(int, int[][], int[]) - Static method in class smile.classification.Maxent

Fits maximum entropy classifier.

binomial(int, int[][], int[], double, double, int) - Static method in class smile.classification.Maxent

Fits maximum entropy classifier.

binomial(int, int[][], int[], Properties) - Static method in class smile.classification.Maxent

Fits maximum entropy classifier.

binomial(SparseDataset<Integer>) - Static method in class smile.classification.SparseLogisticRegression

Fits binomial logistic regression.

binomial(SparseDataset<Integer>, double, double, int) - Static method in class smile.classification.SparseLogisticRegression

Fits binomial logistic regression.

binomial(SparseDataset<Integer>, Properties) - Static method in class smile.classification.SparseLogisticRegression

Fits binomial logistic regression.

Binomial - Interface in smile.glm.model

The response variable is of Binomial distribution.

Binomial(double[], double, double, IntSet) - Constructor for class smile.classification.LogisticRegression.Binomial

Constructor.

Binomial(double[], double, double, IntSet) - Constructor for class smile.classification.Maxent.Binomial

Constructor.

Binomial(double[], double, double, IntSet) - Constructor for class smile.classification.SparseLogisticRegression.Binomial

Constructor.

BinomialDistribution - Class in smile.stat.distribution

The binomial distribution is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p.

BinomialDistribution(int, double) - Constructor for class smile.stat.distribution.BinomialDistribution

Constructor.

BinParams - Class in smile.plot.vega

To test a data point in a filter transform or a test property in conditional encoding, a predicate definition of the following forms must be specified: - a Vega expression string, where datum can be used to refer to the current data object.

BinParams() - Constructor for class smile.plot.vega.BinParams

Constructor.

bins(double[], double) - Static method in interface smile.math.Histogram

Returns the number of bins for a data based on a suggested bin width h.

bins(int) - Static method in interface smile.math.Histogram

Returns the number of bins by square-root rule, which takes the square root of the number of data points in the sample (used by Excel histograms and many others).

BIRCH - Class in smile.vq

Balanced Iterative Reducing and Clustering using Hierarchies.

BIRCH(int, int, int, double) - Constructor for class smile.vq.BIRCH

Constructor.

bits() - Method in class smile.gap.BitString

Returns the bit string of chromosome.

BitString - Class in smile.gap

The standard bit string representation of the solution domain.

BitString(byte[], Fitness<BitString>) - Constructor for class smile.gap.BitString

Constructor.

BitString(byte[], Fitness<BitString>, Crossover, double, double) - Constructor for class smile.gap.BitString

Constructor.

BitString(int, Fitness<BitString>) - Constructor for class smile.gap.BitString

Constructor.

BitString(int, Fitness<BitString>, Crossover, double, double) - Constructor for class smile.gap.BitString

Constructor.

bk() - Method in class smile.math.matrix.fp32.SymmMatrix

Bunch-Kaufman decomposition.

bk() - Method in class smile.math.matrix.SymmMatrix

Bunch-Kaufman decomposition.

BKTree<K,V> - Class in smile.neighbor

A BK-tree is a metric tree specifically adapted to discrete metric spaces.

BKTree(Metric<K>) - Constructor for class smile.neighbor.BKTree

Constructor.

BLACK - Static variable in interface smile.plot.swing.Palette

blas() - Method in enum class smile.math.blas.Diag

Returns the int value for BLAS.

blas() - Method in enum class smile.math.blas.Layout

Returns the int value for BLAS.

blas() - Method in enum class smile.math.blas.Side

Returns the int value for BLAS.

blas() - Method in enum class smile.math.blas.Transpose

Returns the int value for BLAS.

blas() - Method in enum class smile.math.blas.UPLO

Returns the int value for BLAS.

BLAS - Interface in smile.math.blas

Basic Linear Algebra Subprograms.

blend(String) - Method in class smile.plot.vega.Mark

Sets the color blend mode for drawing an item on its current background.

block() - Method in record class smile.vision.layer.MBConvConfig

Returns the value of the block record component.

BLUE - Static variable in interface smile.plot.swing.Palette

BM25 - Class in smile.nlp.relevance

The BM25 weighting scheme, often called Okapi weighting, after the system in which it was first implemented, was developed as a way of building a probabilistic model sensitive to term frequency and document length while not introducing too many additional parameters into the model.

BM25() - Constructor for class smile.nlp.relevance.BM25

Default constructor with k1 = 1.2, b = 0.75, delta = 1.0.

BM25(double, double, double) - Constructor for class smile.nlp.relevance.BM25

Constructor.

body - Variable in class smile.nlp.Text

The text body.

Boolean - Enum constant in enum class smile.data.type.DataType.ID

Boolean type ID.

BOOLEAN - Static variable in interface smile.util.Regex

Boolean regular expression pattern.

BOOLEAN_REGEX - Static variable in interface smile.util.Regex

Boolean regular expression.

BooleanArrayType - Static variable in class smile.data.type.DataTypes

Boolean Array data type.

BooleanObjectType - Static variable in class smile.data.type.DataTypes

Boolean Object data type.

BooleanType - Class in smile.data.type

Boolean data type.

BooleanType - Static variable in class smile.data.type.DataTypes

Boolean data type.

booleanVector(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

booleanVector(int) - Method in class smile.data.IndexDataFrame

booleanVector(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

booleanVector(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

BooleanVector - Interface in smile.data.vector

An immutable boolean vector.

Bootstrap - Interface in smile.validation

The bootstrap is a general tool for assessing statistical accuracy.

bounds(String) - Method in class smile.plot.vega.Concat

bounds(String) - Method in class smile.plot.vega.Facet

bounds(String) - Method in class smile.plot.vega.Repeat

bounds(String) - Method in interface smile.plot.vega.ViewLayoutComposition

Sets the bounds calculation method to use for determining the extent of a sub-plot.

Box_Pierce - Enum constant in enum class smile.timeseries.BoxTest.Type

Box-Pierce test.

boxed() - Method in interface smile.data.type.DataType

Returns the boxed data type if this is a primitive type.

boxed(Collection<Tuple>) - Method in class smile.data.type.StructType

Updates the field type to the boxed one if the field has null/missing values in the data.

BoxPlot - Class in smile.plot.swing

A boxplot is a convenient way of graphically depicting groups of numerical data through their five-number summaries (the smallest observation (sample minimum), lower quartile (Q1), median (Q2), upper quartile (Q3), and largest observation (sample maximum).

BoxPlot(double[][], String[]) - Constructor for class smile.plot.swing.BoxPlot

Constructor.

BoxTest - Class in smile.timeseries

Portmanteau test jointly that several autocorrelations of time series are zero.

BoxTest.Type - Enum Class in smile.timeseries

The type of test.

branch(Tuple) - Method in class smile.base.cart.InternalNode

Returns true if the instance goes to the true branch.

branch(Tuple) - Method in class smile.base.cart.NominalNode

branch(Tuple) - Method in class smile.base.cart.OrdinalNode

BreakIteratorSentenceSplitter - Class in smile.nlp.tokenizer

A sentence splitter based on the java.text.BreakIterator, which supports multiple natural languages (selected by locale setting).

BreakIteratorSentenceSplitter() - Constructor for class smile.nlp.tokenizer.BreakIteratorSentenceSplitter

Constructor for the default locale.

BreakIteratorSentenceSplitter(Locale) - Constructor for class smile.nlp.tokenizer.BreakIteratorSentenceSplitter

Constructor for the given locale.

BreakIteratorTokenizer - Class in smile.nlp.tokenizer

A word tokenizer based on the java.text.BreakIterator, which supports multiple natural languages (selected by locale setting).

BreakIteratorTokenizer() - Constructor for class smile.nlp.tokenizer.BreakIteratorTokenizer

Constructor for the default locale.

BreakIteratorTokenizer(Locale) - Constructor for class smile.nlp.tokenizer.BreakIteratorTokenizer

Constructor for the given locale.

breaks - Variable in class smile.feature.selection.InformationValue

Breakpoints of intervals for numerical variables.

breaks(double[], double) - Static method in interface smile.math.Histogram

Returns the breakpoints between histogram cells for a dataset based on a suggested bin width h.

breaks(double[], int) - Static method in interface smile.math.Histogram

Returns the breakpoints between histogram cells for a dataset.

breaks(double, double, double) - Static method in interface smile.math.Histogram

Returns the breakpoints between histogram cells for a given range based on a suggested bin width h.

breaks(double, double, int) - Static method in interface smile.math.Histogram

Returns the breakpoints between histogram cells for a given range.

BROWN - Static variable in interface smile.plot.swing.Palette

bubble(int) - Static method in interface smile.vq.Neighborhood

Returns the bubble neighborhood function.

bucket - Variable in class smile.neighbor.lsh.Bucket

The bucket id is given by the universal bucket hashing.

Bucket - Class in smile.neighbor.lsh

A bucket is a container for points that all have the same value for hash function g (function g is a vector of k LSH functions).

Bucket(int) - Constructor for class smile.neighbor.lsh.Bucket

Constructor.

build() - Method in class smile.hash.PerfectMap.Builder

Builds the perfect map.

build(int) - Method in class smile.base.mlp.HiddenLayerBuilder

build(int) - Method in class smile.base.mlp.LayerBuilder

Builds a layer.

build(int) - Method in class smile.base.mlp.OutputLayerBuilder

builder(String, int, double, double) - Static method in class smile.base.mlp.Layer

Returns a hidden layer.

Builder() - Constructor for class smile.hash.PerfectMap.Builder

Constructor.

Builder(Map<String, T>) - Constructor for class smile.hash.PerfectMap.Builder

Constructor.

BunchKaufman(SymmMatrix, int[], int) - Constructor for class smile.math.matrix.fp32.SymmMatrix.BunchKaufman

Constructor.

BunchKaufman(SymmMatrix, int[], int) - Constructor for class smile.math.matrix.SymmMatrix.BunchKaufman

Constructor.

BURGUNDY - Static variable in interface smile.plot.swing.Palette

Button - Class in smile.swing

Action initialized JButton.

Button(Action) - Constructor for class smile.swing.Button

Constructor.

ButtonCellRenderer - Class in smile.swing.table

The ButtonCellRenderer class provides a renderer and an editor that looks like a JButton.

ButtonCellRenderer(JTable, Action, int) - Constructor for class smile.swing.table.ButtonCellRenderer

Create the ButtonCellRenderer to be used as a renderer and editor.

Byte - Enum constant in enum class smile.data.type.DataType.ID

Byte type ID.

ByteArrayCellRenderer - Class in smile.swing.table

Byte array renderer in JTable.

ByteArrayCellRenderer() - Constructor for class smile.swing.table.ByteArrayCellRenderer

Constructor.

ByteArrayType - Static variable in class smile.data.type.DataTypes

Byte Array data type.

ByteObjectType - Static variable in class smile.data.type.DataTypes

Byte Object data type.

Bytes - Record Class in smile.util

Byte string.

Bytes(byte[]) - Constructor for record class smile.util.Bytes

Creates an instance of a Bytes record class.

Bytes(String) - Constructor for record class smile.util.Bytes

Constructor with a string input.

ByteType - Class in smile.data.type

Byte data type.

ByteType - Static variable in class smile.data.type.DataTypes

Byte data type.

byteValue() - Method in class smile.deep.tensor.Tensor

Returns the byte value when the tensor holds a single value.

byteVector(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

byteVector(int) - Method in class smile.data.IndexDataFrame

byteVector(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

byteVector(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

ByteVector - Interface in smile.data.vector

An immutable byte vector.

C

c(double...) - Static method in class smile.math.MathEx

Combines the arguments to form a vector.

c(double[]...) - Static method in class smile.math.MathEx

Concatenates multiple vectors into one.

c(float...) - Static method in class smile.math.MathEx

Combines the arguments to form a vector.

c(float[]...) - Static method in class smile.math.MathEx

Concatenates multiple vectors into one.

c(int...) - Static method in class smile.math.MathEx

Combines the arguments to form a vector.

c(int[]...) - Static method in class smile.math.MathEx

Concatenates multiple vectors into one.

c(String...) - Static method in class smile.math.MathEx

Combines the arguments to form a vector.

c(String[]...) - Static method in class smile.math.MathEx

Concatenates multiple vectors into one array of strings.

CacheFiles - Interface in smile.util

Static methods that manage cache files.

CADET_BLUE - Static variable in interface smile.plot.swing.Palette

calculate(String, String) - Method in class smile.plot.vega.Transform

Adds a formula transform extends data objects with new fields (columns) according to an expression.

CANCEL_OPTION - Static variable in class smile.swing.FontChooser

Return value from showDialog().

canvas() - Method in class smile.plot.swing.BarPlot

canvas() - Method in class smile.plot.swing.BoxPlot

canvas() - Method in class smile.plot.swing.Contour

canvas() - Method in class smile.plot.swing.Dendrogram

canvas() - Method in class smile.plot.swing.Heatmap

canvas() - Method in class smile.plot.swing.Hexmap

canvas() - Method in class smile.plot.swing.LinePlot

canvas() - Method in class smile.plot.swing.Plot

Returns a canvas of the plot.

canvas() - Method in class smile.plot.swing.ScreePlot

canvas() - Method in class smile.plot.swing.SparseMatrixPlot

canvas() - Method in class smile.plot.swing.StaircasePlot

Canvas - Class in smile.plot.swing

Canvas for mathematical plots.

Canvas(double[], double[]) - Constructor for class smile.plot.swing.Canvas

Constructor

Canvas(double[], double[], boolean) - Constructor for class smile.plot.swing.Canvas

Constructor

CARDINAL_NUMBER - Static variable in interface smile.util.Regex

Cardinal numbers.

CARDINAL_NUMBER_WITH_COMMA - Static variable in interface smile.util.Regex

Cardinal numbers, optionally thousands are separated by comma.

CART - Class in smile.base.cart

Classification and regression tree.

CART(DataFrame, StructField, int, int, int, int, int[], int[][]) - Constructor for class smile.base.cart.CART

Constructor.

CART(Formula, StructType, StructField, Node, double[]) - Constructor for class smile.base.cart.CART

Constructor.

CategoricalEncoder - Enum Class in smile.data

Categorical variable encoder.

CategoricalMeasure - Class in smile.data.measure

Categorical data can be stored into groups or categories with the aid of names or labels.

CategoricalMeasure(int[]) - Constructor for class smile.data.measure.CategoricalMeasure

Constructor.

CategoricalMeasure(int[], String[]) - Constructor for class smile.data.measure.CategoricalMeasure

Constructor.

CategoricalMeasure(String...) - Constructor for class smile.data.measure.CategoricalMeasure

Constructor.

CategoricalMeasure(List<String>) - Constructor for class smile.data.measure.CategoricalMeasure

Constructor.

cbind(double[]...) - Static method in class smile.math.MathEx

Concatenates vectors by columns.

cbind(float[]...) - Static method in class smile.math.MathEx

Concatenates vectors by columns.

cbind(int[]...) - Static method in class smile.math.MathEx

Concatenates vectors by columns.

cbind(String[]...) - Static method in class smile.math.MathEx

Concatenates vectors by columns.

cbrt(String) - Static method in interface smile.data.formula.Terms

The cbrt(x) term.

cbrt(Term) - Static method in interface smile.data.formula.Terms

The cbrt(x) term.

CC - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Coordinating conjunction.

CD - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Cardinal number.

cdf(double) - Method in class smile.stat.distribution.BernoulliDistribution

cdf(double) - Method in class smile.stat.distribution.BetaDistribution

cdf(double) - Method in class smile.stat.distribution.BinomialDistribution

cdf(double) - Method in class smile.stat.distribution.ChiSquareDistribution

cdf(double) - Method in class smile.stat.distribution.DiscreteMixture

cdf(double) - Method in interface smile.stat.distribution.Distribution

Cumulative distribution function.

cdf(double) - Method in class smile.stat.distribution.EmpiricalDistribution

cdf(double) - Method in class smile.stat.distribution.ExponentialDistribution

cdf(double) - Method in class smile.stat.distribution.FDistribution

cdf(double) - Method in class smile.stat.distribution.GammaDistribution

cdf(double) - Method in class smile.stat.distribution.GaussianDistribution

cdf(double) - Method in class smile.stat.distribution.GeometricDistribution

cdf(double) - Method in class smile.stat.distribution.HyperGeometricDistribution

cdf(double) - Method in class smile.stat.distribution.KernelDensity

Cumulative distribution function.

cdf(double) - Method in class smile.stat.distribution.LogisticDistribution

cdf(double) - Method in class smile.stat.distribution.LogNormalDistribution

cdf(double) - Method in class smile.stat.distribution.Mixture

cdf(double) - Method in class smile.stat.distribution.NegativeBinomialDistribution

cdf(double) - Method in class smile.stat.distribution.PoissonDistribution

cdf(double) - Method in class smile.stat.distribution.ShiftedGeometricDistribution

cdf(double) - Method in class smile.stat.distribution.TDistribution

cdf(double) - Method in class smile.stat.distribution.WeibullDistribution

cdf(double[]) - Method in interface smile.stat.distribution.MultivariateDistribution

Cumulative distribution function.

cdf(double[]) - Method in class smile.stat.distribution.MultivariateGaussianDistribution

Algorithm from Alan Genz (1992) Numerical Computation of Multivariate Normal Probabilities, Journal of Computational and Graphical Statistics, pp.

cdf(double[]) - Method in class smile.stat.distribution.MultivariateMixture

cdf2tailed(double) - Method in class smile.stat.distribution.TDistribution

Two-tailed cdf.

ceil(String) - Static method in interface smile.data.formula.Terms

The ceil(x) term.

ceil(Term) - Static method in interface smile.data.formula.Terms

The ceil(x) term.

center() - Method in class smile.feature.extraction.PCA

Returns the center of data.

center() - Method in class smile.feature.extraction.ProbabilisticPCA

Returns the center of data.

center(boolean) - Method in class smile.plot.vega.Concat

center(boolean) - Method in class smile.plot.vega.Facet

center(boolean) - Method in class smile.plot.vega.FacetField

Sets if facet's subviews should be centered relative to their respective rows or columns.

center(boolean) - Method in class smile.plot.vega.Repeat

center(boolean) - Method in interface smile.plot.vega.ViewLayoutComposition

Sets if subviews should be centered relative to their respective rows or columns.

center(double, double) - Method in class smile.plot.vega.Projection

Sets the projection's center, a two-element array of longitude and latitude in degrees.

center(int, int) - Method in class smile.plot.vega.Concat

center(int, int) - Method in class smile.plot.vega.Facet

center(int, int) - Method in class smile.plot.vega.Repeat

center(int, int) - Method in interface smile.plot.vega.ViewLayoutComposition

Sets if subviews should be centered relative to their respective rows or columns.

CentroidClustering<T,U> - Class in smile.clustering

In centroid-based clustering, clusters are represented by a central vector, which may not necessarily be a member of the data set.

CentroidClustering(double, T[], int[]) - Constructor for class smile.clustering.CentroidClustering

Constructor.

centroids - Variable in class smile.clustering.CentroidClustering

The centroids of each cluster.

centroids() - Method in class smile.vq.BIRCH

Returns the cluster centroids of leaf nodes.

change(int) - Method in class smile.util.PriorityQueue

The priority of item k has changed.

Char - Enum constant in enum class smile.data.type.DataType.ID

Char type ID.

CharArrayType - Static variable in class smile.data.type.DataTypes

Char Array data type.

CharObjectType - Static variable in class smile.data.type.DataTypes

Char Object data type.

charset(Charset) - Method in class smile.io.CSV

Sets the charset.

charset(Charset) - Method in class smile.io.JSON

Sets the charset.

CharType - Class in smile.data.type

Char data type.

CharType - Static variable in class smile.data.type.DataTypes

Char data type.

charVector(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

charVector(int) - Method in class smile.data.IndexDataFrame

charVector(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

charVector(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

CharVector - Interface in smile.data.vector

An immutable char vector.

ChebyshevDistance - Class in smile.math.distance

Chebyshev distance (or Tchebychev distance), or L_∞ metric is a metric defined on a vector space where the distance between two vectors is the greatest of their differences along any coordinate dimension.

ChebyshevDistance() - Constructor for class smile.math.distance.ChebyshevDistance

Constructor.

children() - Method in class smile.taxonomy.Concept

Gets all children concepts.

chisq - Variable in class smile.stat.hypothesis.ChiSqTest

chi-square statistic

ChiSqTest - Class in smile.stat.hypothesis

Pearson's chi-square test, also known as the chi-square goodness-of-fit test or chi-square test for independence.

ChiSqTest(String, double, double, double) - Constructor for class smile.stat.hypothesis.ChiSqTest

Constructor.

ChiSqTest(String, double, double, double, double) - Constructor for class smile.stat.hypothesis.ChiSqTest

Constructor.

ChiSquareDistribution - Class in smile.stat.distribution

Chi-square (or chi-squared) distribution with k degrees of freedom is the distribution of a sum of the squares of k independent standard normal random variables.

ChiSquareDistribution(int) - Constructor for class smile.stat.distribution.ChiSquareDistribution

Constructor.

cholesky() - Method in class smile.math.matrix.BandMatrix

Cholesky decomposition for symmetric and positive definite matrix.

cholesky() - Method in class smile.math.matrix.BigMatrix

Cholesky decomposition for symmetric and positive definite matrix.

cholesky() - Method in class smile.math.matrix.fp32.BandMatrix

Cholesky decomposition for symmetric and positive definite matrix.

cholesky() - Method in class smile.math.matrix.fp32.Matrix

Cholesky decomposition for symmetric and positive definite matrix.

cholesky() - Method in class smile.math.matrix.fp32.SymmMatrix

Cholesky decomposition for symmetric and positive definite matrix.

cholesky() - Method in class smile.math.matrix.Matrix

Cholesky decomposition for symmetric and positive definite matrix.

cholesky() - Method in class smile.math.matrix.SymmMatrix

Cholesky decomposition for symmetric and positive definite matrix.

cholesky(boolean) - Method in class smile.math.matrix.BigMatrix

Cholesky decomposition for symmetric and positive definite matrix.

cholesky(boolean) - Method in class smile.math.matrix.fp32.Matrix

Cholesky decomposition for symmetric and positive definite matrix.

cholesky(boolean) - Method in class smile.math.matrix.Matrix

Cholesky decomposition for symmetric and positive definite matrix.

Cholesky(BandMatrix) - Constructor for class smile.math.matrix.BandMatrix.Cholesky

Constructor.

Cholesky(BigMatrix) - Constructor for class smile.math.matrix.BigMatrix.Cholesky

Constructor.

Cholesky(BandMatrix) - Constructor for class smile.math.matrix.fp32.BandMatrix.Cholesky

Constructor.

Cholesky(Matrix) - Constructor for class smile.math.matrix.fp32.Matrix.Cholesky

Constructor.

Cholesky(SymmMatrix) - Constructor for class smile.math.matrix.fp32.SymmMatrix.Cholesky

Constructor.

Cholesky(Matrix) - Constructor for class smile.math.matrix.Matrix.Cholesky

Constructor.

Cholesky(SymmMatrix) - Constructor for class smile.math.matrix.SymmMatrix.Cholesky

Constructor.

CholeskyOfAtA() - Method in class smile.math.matrix.BigMatrix.QR

Returns the Cholesky decomposition of A'A.

CholeskyOfAtA() - Method in class smile.math.matrix.fp32.Matrix.QR

Returns the Cholesky decomposition of A'A.

CholeskyOfAtA() - Method in class smile.math.matrix.Matrix.QR

Returns the Cholesky decomposition of A'A.

choose(int, int) - Static method in class smile.math.MathEx

The n choose k.

Chromosome - Interface in smile.gap

Artificial chromosomes in genetic algorithm/programming encoding candidate solutions to an optimization problem.

CLARANS<T> - Class in smile.clustering

Clustering Large Applications based upon RANdomized Search.

CLARANS(double, T[], int[], Distance<T>) - Constructor for class smile.clustering.CLARANS

Constructor.

classes - Variable in class smile.classification.AbstractClassifier

The class labels.

classes - Variable in class smile.classification.ClassLabels

The class labels.

classes() - Method in class smile.classification.AbstractClassifier

classes() - Method in interface smile.classification.Classifier

Returns the class labels.

classes() - Method in class smile.classification.DecisionTree

classes() - Method in class smile.classification.MLP

classes() - Method in class smile.classification.SVM

classification(int, int) - Static method in interface smile.vision.transform.Transform

Returns a transform for image classification.

classification(int, int, float[], float[], int) - Static method in interface smile.vision.transform.Transform

Returns a transform for image classification.

classification(int, int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.CrossValidation

Repeated cross validation of classification.

classification(int, int, T[], int[], BiFunction<T[], int[], M>) - Static method in interface smile.validation.CrossValidation

Repeated cross validation of classification.

classification(int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.Bootstrap

Runs classification bootstrap validation.

classification(int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.CrossValidation

Cross validation of classification.

classification(int, T[], int[], BiFunction<T[], int[], M>) - Static method in interface smile.validation.Bootstrap

Runs classification bootstrap validation.

classification(int, T[], int[], BiFunction<T[], int[], M>) - Static method in interface smile.validation.CrossValidation

Cross validation of classification.

classification(Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in interface smile.validation.LOOCV

Runs leave-one-out cross validation tests.

classification(T[], int[], BiFunction<T[], int[], M>) - Static method in interface smile.validation.LOOCV

Runs leave-one-out cross validation tests.

CLASSIFICATION_ERROR - Enum constant in enum class smile.base.cart.SplitRule

Classification error.

ClassificationMetric - Interface in smile.validation.metric

An abstract interface to measure the classification performance.

ClassificationMetrics - Class in smile.validation

The classification validation metrics.

ClassificationMetrics(double, double, int, int, double) - Constructor for class smile.validation.ClassificationMetrics

Constructor.

ClassificationMetrics(double, double, int, int, double, double) - Constructor for class smile.validation.ClassificationMetrics

Constructor of multiclass soft classifier validation.

ClassificationMetrics(double, double, int, int, double, double, double, double, double, double) - Constructor for class smile.validation.ClassificationMetrics

Constructor of binary classifier validation.

ClassificationMetrics(double, double, int, int, double, double, double, double, double, double, double, double) - Constructor for class smile.validation.ClassificationMetrics

Constructor of binary soft classifier validation.

ClassificationMetrics(double, double, int, int, double, double, double, double, double, double, double, double, double) - Constructor for class smile.validation.ClassificationMetrics

Constructor.

ClassificationValidation<M> - Class in smile.validation

Classification model validation results.

ClassificationValidation(M, double, double, int[], int[]) - Constructor for class smile.validation.ClassificationValidation

Constructor.

ClassificationValidation(M, double, double, int[], int[], double[][]) - Constructor for class smile.validation.ClassificationValidation

Constructor of soft classifier validation.

ClassificationValidations<M> - Class in smile.validation

Classification model validation results.

ClassificationValidations(List<ClassificationValidation<M>>) - Constructor for class smile.validation.ClassificationValidations

Constructor.

Classifier<T> - Interface in smile.classification

A classifier assigns an input object into one of a given number of categories.

Classifier.Trainer<T,M> - Interface in smile.classification

The classifier trainer.

ClassLabels - Class in smile.classification

Map arbitrary class labels to [0, k), where k is the number of classes.

ClassLabels(int, int[], IntSet) - Constructor for class smile.classification.ClassLabels

Constructor.

clean() - Static method in interface smile.util.CacheFiles

Cleans up the cache directory.

clear() - Method in class smile.base.cart.CART

Clear the workspace of building tree.

clear() - Method in class smile.plot.swing.Canvas

Remove all graphic plots from the canvas.

clear() - Method in class smile.util.DoubleArrayList

Removes all the values from this list.

clear() - Method in class smile.util.IntArrayList

Removes all the values from this list.

clear(double) - Method in class smile.vq.NeuralMap

Removes staled neurons and the edges beyond lifetime.

clearClip() - Method in class smile.plot.swing.Graphics

Clear the restriction of the draw area.

clip() - Method in class smile.plot.swing.Graphics

Restrict the draw area to the valid base coordinate space.

clip(boolean) - Method in class smile.plot.vega.Mark

Sets whether a mark be clipped to the enclosing group's width and height.

clipAngle(double) - Method in class smile.plot.vega.Projection

Sets the projection's clipping circle radius to the specified angle in degrees.

clipExtent(double, double, double, double) - Method in class smile.plot.vega.Projection

Sets the projection's viewport clip extent to the specified bounds in pixels.

clipHeight(double) - Method in class smile.plot.vega.Legend

Sets the height in pixels to clip symbol legend entries and limit their size.

clipNorm - Variable in class smile.base.mlp.MultilayerPerceptron

The gradient clipping norm.

clipValue - Variable in class smile.base.mlp.MultilayerPerceptron

The gradient clipping value.

clone() - Method in class smile.deep.tensor.Tensor

clone() - Method in class smile.math.matrix.BandMatrix

clone() - Method in class smile.math.matrix.BigMatrix

Returns a deep copy of matrix.

clone() - Method in class smile.math.matrix.fp32.BandMatrix

clone() - Method in class smile.math.matrix.fp32.Matrix

Returns a deep copy of matrix.

clone() - Method in class smile.math.matrix.fp32.SparseMatrix

clone() - Method in class smile.math.matrix.fp32.SymmMatrix

clone() - Method in class smile.math.matrix.Matrix

Returns a deep copy of matrix.

clone() - Method in class smile.math.matrix.SparseMatrix

clone() - Method in class smile.math.matrix.SymmMatrix

clone() - Method in class smile.neighbor.lsh.Probe

clone(double[][]) - Static method in class smile.math.MathEx

Deep clone a two-dimensional array.

clone(float[][]) - Static method in class smile.math.MathEx

Deep clone a two-dimensional array.

clone(int[][]) - Static method in class smile.math.MathEx

Deep clone a two-dimensional array.

close() - Method in class smile.data.SQL

close() - Method in record class smile.deep.SampleBatch

close() - Method in class smile.deep.tensor.Tensor

close() - Method in class smile.io.Arff

close() - Method in class smile.util.AutoScope

CLOSING_PARENTHESIS - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Punctuation ) ] }

CLOSING_QUOTATION - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Punctuation ' or ''

clustering(double[][], double[][], int[], int[]) - Method in class smile.clustering.BBDTree

Given k cluster centroids, this method assigns data to nearest centroids.

ClusteringMetric - Interface in smile.validation.metric

An abstract interface to measure the clustering performance.

CNB - Enum constant in enum class smile.classification.DiscreteNaiveBayes.Model

Complement Naive Bayes.

coefficients() - Method in class smile.classification.LogisticRegression.Binomial

Returns an array of size (p+1) containing the linear weights of binary logistic regression, where p is the dimension of feature vectors.

coefficients() - Method in class smile.classification.LogisticRegression.Multinomial

Returns a 2d-array of size (k-1) x (p+1), containing the linear weights of multi-class logistic regression, where k is the number of classes and p is the dimension of feature vectors.

coefficients() - Method in class smile.classification.Maxent.Binomial

Returns an array of size (p+1) containing the linear weights of binary logistic regression, where p is the dimension of feature vectors.

coefficients() - Method in class smile.classification.Maxent.Multinomial

Returns a 2d-array of size (k-1) x (p+1), containing the linear weights of multi-class logistic regression, where k is the number of classes and p is the dimension of feature vectors.

coefficients() - Method in class smile.classification.SparseLogisticRegression.Binomial

Returns an array of size (p+1) containing the linear weights of binary logistic regression, where p is the dimension of feature vectors.

coefficients() - Method in class smile.classification.SparseLogisticRegression.Multinomial

Returns a 2d-array of size (k-1) x (p+1), containing the linear weights of multi-class logistic regression, where k is the number of classes and p is the dimension of feature vectors.

coefficients() - Method in class smile.glm.GLM

Returns an array of size (p+1) containing the linear weights of binary logistic regression, where p is the dimension of feature vectors.

coefficients() - Method in class smile.regression.LinearModel

Returns the linear coefficients without intercept.

coerce(DataType, DataType) - Static method in interface smile.data.type.DataType

Returns the common type.

CoifletWavelet - Class in smile.wavelet

Coiflet wavelets.

CoifletWavelet(int) - Constructor for class smile.wavelet.CoifletWavelet

Constructor.

col(int) - Method in class smile.math.matrix.BigMatrix

Returns the j-th column.

col(int) - Method in class smile.math.matrix.fp32.Matrix

Returns the j-th column.

col(int) - Method in class smile.math.matrix.Matrix

Returns the j-th column.

col(int...) - Method in class smile.math.matrix.BigMatrix

Returns the matrix of selected columns.

COL_MAJOR - Enum constant in enum class smile.math.blas.Layout

Column major layout.

collect() - Static method in interface smile.data.DataFrame.Collectors

Returns a stream collector that accumulates tuples into a DataFrame.

collect(Class<T>) - Static method in interface smile.data.DataFrame.Collectors

Returns a stream collector that accumulates objects into a DataFrame.

collector() - Static method in interface smile.data.Dataset

Returns a stream collector that accumulates elements into a Dataset.

collector() - Static method in class smile.math.matrix.Matrix

Returns a stream collector that accumulates elements into a Matrix.

colMax(double[][]) - Static method in class smile.math.MathEx

Returns the column maximum of a matrix.

colMax(int[][]) - Static method in class smile.math.MathEx

Returns the column maximum of a matrix.

colMeans() - Method in class smile.math.matrix.BigMatrix

Returns the mean of each column.

colMeans() - Method in class smile.math.matrix.fp32.Matrix

Returns the mean of each column.

colMeans() - Method in class smile.math.matrix.Matrix

Returns the mean of each column.

colMeans(double[][]) - Static method in class smile.math.MathEx

Returns the column means of a matrix.

colMin(double[][]) - Static method in class smile.math.MathEx

Returns the column minimum of a matrix.

colMin(int[][]) - Static method in class smile.math.MathEx

Returns the column minimum of a matrix.

colName(int) - Method in class smile.math.matrix.fp32.IMatrix

Returns the name of i-th column.

colName(int) - Method in class smile.math.matrix.IMatrix

Returns the name of i-th column.

colNames() - Method in class smile.math.matrix.fp32.IMatrix

Returns the column names.

colNames() - Method in class smile.math.matrix.IMatrix

Returns the column names.

colNames(String[]) - Method in class smile.math.matrix.fp32.IMatrix

Sets the column names.

colNames(String[]) - Method in class smile.math.matrix.IMatrix

Sets the column names.

Colon - Static variable in class smile.deep.tensor.Index

The colon (:) is used to slice all elements of a dimension.

COLON - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Punctuation ; : ...

color(String) - Method in class smile.plot.vega.Mark

Sets the default color.

ColorCellEditor - Class in smile.swing.table

Color editor in JTable.

ColorCellEditor() - Constructor for class smile.swing.table.ColorCellEditor

Constructor.

ColorCellRenderer - Class in smile.swing.table

Color renderer in JTable.

ColorCellRenderer() - Constructor for class smile.swing.table.ColorCellRenderer

Constructor.

ColorCellRenderer(boolean) - Constructor for class smile.swing.table.ColorCellRenderer

Constructor.

COLORS - Static variable in interface smile.plot.swing.Palette

cols(int...) - Method in class smile.math.matrix.fp32.Matrix

Returns the matrix of selected columns.

cols(int...) - Method in class smile.math.matrix.Matrix

Returns the matrix of selected columns.

colSds() - Method in class smile.math.matrix.BigMatrix

Returns the standard deviations of each column.

colSds() - Method in class smile.math.matrix.fp32.Matrix

Returns the standard deviations of each column.

colSds() - Method in class smile.math.matrix.Matrix

Returns the standard deviations of each column.

colSds(double[][]) - Static method in class smile.math.MathEx

Returns the column standard deviations of a matrix.

colSums() - Method in class smile.math.matrix.BigMatrix

Returns the sum of each column.

colSums() - Method in class smile.math.matrix.fp32.Matrix

Returns the sum of each column.

colSums() - Method in class smile.math.matrix.Matrix

Returns the sum of each column.

colSums(double[][]) - Static method in class smile.math.MathEx

Returns the column sums of a matrix.

colSums(int[][]) - Static method in class smile.math.MathEx

Returns the column sums of a matrix.

column(double[]) - Static method in class smile.math.matrix.BigMatrix

Returns a column vector/matrix.

column(double[]) - Static method in class smile.math.matrix.fp32.Matrix

Returns a column vector/matrix.

column(double[]) - Static method in class smile.math.matrix.Matrix

Returns a column vector/matrix.

column(double[], int, int) - Static method in class smile.math.matrix.BigMatrix

Returns a column vector/matrix.

column(double[], int, int) - Static method in class smile.math.matrix.fp32.Matrix

Returns a column vector/matrix.

column(double[], int, int) - Static method in class smile.math.matrix.Matrix

Returns a column vector/matrix.

column(float[]) - Static method in class smile.math.matrix.fp32.Matrix

Returns a column vector/matrix.

column(float[], int, int) - Static method in class smile.math.matrix.fp32.Matrix

Returns a column vector/matrix.

column(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

column(int) - Method in class smile.data.IndexDataFrame

column(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

column(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

column(String) - Method in class smile.plot.vega.Facet

Returns the field definition for the vertical facet of trellis plots.

columnAdded(TableColumnModelEvent) - Method in class smile.swing.table.TableColumnSettings

columnMarginChanged(ChangeEvent) - Method in class smile.swing.table.TableColumnSettings

columnMoved(TableColumnModelEvent) - Method in class smile.swing.table.TableColumnSettings

columnPadding(double) - Method in class smile.plot.vega.Legend

Sets the horizontal padding in pixels between symbol legend entries.

columnRemoved(TableColumnModelEvent) - Method in class smile.swing.table.TableColumnSettings

columns - Variable in class smile.feature.extraction.Projection

The fields of input space.

columns(int) - Method in class smile.plot.vega.Facet

Sets the number of columns to include in the view composition layout.

columns(int) - Method in class smile.plot.vega.Legend

Sets the number of columns in which to arrange symbol legend entries.

columns(int) - Method in class smile.plot.vega.Repeat

Sets the number of columns to include in the view composition layout.

columnSelectionChanged(ListSelectionEvent) - Method in class smile.swing.table.TableColumnSettings

ColumnTransform - Class in smile.data.transform

Column-wise data transformation.

ColumnTransform(String, Map<String, Function>) - Constructor for class smile.data.transform.ColumnTransform

Constructor.

COMMA - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Punctuation ,

COMPACT - Enum constant in enum class smile.math.blas.SVDJob

The first min(m, n) singular vectors are returned in supplied matrix U (or Vt).

comparator - Static variable in class smile.base.cart.Split

The comparator on the split score.

compareTo(CentroidClustering<T, U>) - Method in class smile.clustering.CentroidClustering

compareTo(MEC<T>) - Method in class smile.clustering.MEC

compareTo(InformationValue) - Method in class smile.feature.selection.InformationValue

compareTo(SignalNoiseRatio) - Method in class smile.feature.selection.SignalNoiseRatio

compareTo(SumSquaresRatio) - Method in class smile.feature.selection.SumSquaresRatio

compareTo(Chromosome) - Method in class smile.gap.BitString

compareTo(PrH) - Method in class smile.neighbor.lsh.PrH

compareTo(Probe) - Method in class smile.neighbor.lsh.Probe

compareTo(PrZ) - Method in class smile.neighbor.lsh.PrZ

compareTo(Neighbor<K, V>) - Method in class smile.neighbor.Neighbor

compareTo(Bigram) - Method in class smile.nlp.collocation.Bigram

compareTo(NGram) - Method in class smile.nlp.collocation.NGram

compareTo(Relevance) - Method in class smile.nlp.relevance.Relevance

compareTo(Neuron) - Method in class smile.vq.hebb.Neuron

CompleteLinkage - Class in smile.clustering.linkage

Complete linkage.

CompleteLinkage(double[][]) - Constructor for class smile.clustering.linkage.CompleteLinkage

Constructor.

CompleteLinkage(int, float[]) - Constructor for class smile.clustering.linkage.CompleteLinkage

Constructor.

Complex - Class in smile.math

Complex number.

Complex(double, double) - Constructor for class smile.math.Complex

Constructor.

Complex.Array - Class in smile.math

Packed array of complex numbers for better memory efficiency.

Component(double, DiscreteDistribution) - Constructor for class smile.stat.distribution.DiscreteMixture.Component

Constructor.

Component(double, Distribution) - Constructor for class smile.stat.distribution.Mixture.Component

Constructor.

Component(double, MultivariateDistribution) - Constructor for class smile.stat.distribution.MultivariateMixture.Component

Constructor.

components - Variable in class smile.ica.ICA

The independent components (row-wise).

components - Variable in class smile.stat.distribution.DiscreteMixture

The components of finite mixture model.

components - Variable in class smile.stat.distribution.Mixture

The components of finite mixture model.

components - Variable in class smile.stat.distribution.MultivariateMixture

The components of finite mixture model.

compose(Transform) - Method in interface smile.data.transform.Transform

Returns a composed function that first applies the before function to its input, and then applies this function to the result.

COMPREHENSIVE - Enum constant in enum class smile.nlp.dictionary.EnglishStopWords

A very long list of stop words.

compute() - Method in class smile.deep.metric.Accuracy

compute() - Method in interface smile.deep.metric.Metric

Computes the metric value from the metric state, which are updated by previous update() calls.

compute() - Method in class smile.deep.metric.Precision

compute() - Method in class smile.deep.metric.Recall

computeGradient(double[]) - Method in class smile.base.mlp.InputLayer

computeGradient(double[]) - Method in class smile.base.mlp.Layer

Computes the parameter gradient for a sample of (mini-)batch.

computeGradientUpdate(double[], double, double, double) - Method in class smile.base.mlp.InputLayer

computeGradientUpdate(double[], double, double, double) - Method in class smile.base.mlp.Layer

Computes the parameter gradient and update the weights.

computeOutputGradient(double[], double) - Method in class smile.base.mlp.OutputLayer

Compute the network output gradient.

Concat - Class in smile.plot.vega

Concatenating views.

Concat(int, VegaLite...) - Constructor for class smile.plot.vega.Concat

Constructor to put multiple views into a flexible flow layout.

Concept - Class in smile.taxonomy

Concept is a set of synonyms, i.e.

Concept(Concept, String...) - Constructor for class smile.taxonomy.Concept

Constructor.

CONCISE - Enum constant in enum class smile.nlp.dictionary.EnglishDictionary

A concise dictionary of common terms in English.

condition() - Method in class smile.math.matrix.BigMatrix.SVD

Returns the L₂ norm condition number, which is max(S) / min(S).

condition() - Method in class smile.math.matrix.fp32.Matrix.SVD

Returns the L₂ norm condition number, which is max(S) / min(S).

condition() - Method in class smile.math.matrix.Matrix.SVD

Returns the L₂ norm condition number, which is max(S) / min(S).

confidence - Variable in class smile.association.AssociationRule

The confidence value.

config() - Method in class smile.plot.vega.VegaLite

Returns the configuration object that lists properties of a visualization for creating a consistent theme.

Config - Class in smile.plot.vega

Vega-Lite's config object lists configuration properties of a visualization for creating a consistent theme.

confusion - Variable in class smile.validation.ClassificationValidation

The confusion matrix.

ConfusionMatrix - Class in smile.validation.metric

The confusion matrix of truth and predictions.

ConfusionMatrix(int[][]) - Constructor for class smile.validation.metric.ConfusionMatrix

Constructor.

conjugate() - Method in class smile.math.Complex

Returns the conjugate.

CONJUGATE_TRANSPOSE - Enum constant in enum class smile.math.blas.Transpose

Conjugate transpose operation on the matrix.

consequent - Variable in class smile.association.AssociationRule

Consequent itemset.

constant(double) - Static method in interface smile.math.TimeFunction

Returns the constant learning rate.

Constant - Class in smile.data.formula

A constant value in the formula.

Constant() - Constructor for class smile.data.formula.Constant

contains(double[][], double[]) - Static method in class smile.math.MathEx

Determines if the polygon contains the point.

contains(double[][], double, double) - Static method in class smile.math.MathEx

Determines if the polygon contains the point.

contains(int) - Method in class smile.util.IntHashSet

Returns true if this set contains the specified element.

contains(String) - Method in interface smile.nlp.dictionary.Dictionary

Returns true if this dictionary contains the specified word.

contains(String) - Method in enum class smile.nlp.dictionary.EnglishDictionary

contains(String) - Method in class smile.nlp.dictionary.EnglishPunctuations

contains(String) - Method in enum class smile.nlp.dictionary.EnglishStopWords

contains(String) - Method in class smile.nlp.dictionary.SimpleDictionary

ContingencyTable - Class in smile.validation.metric

The contingency table.

ContingencyTable(int[], int[]) - Constructor for class smile.validation.metric.ContingencyTable

Constructor.

continuousHeight(int) - Method in class smile.plot.vega.ViewConfig

Sets the default height when the plot has a continuous field for y or latitude, or has arc marks.

continuousWidth(int) - Method in class smile.plot.vega.ViewConfig

Sets the default width when the plot has a continuous field for x or longitude, or has arc marks.

Contour - Class in smile.plot.swing

A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format.

Contour(double[][], double[]) - Constructor for class smile.plot.swing.Contour

Constructor.

Contour(double[][], int, boolean) - Constructor for class smile.plot.swing.Contour

Constructor.

Contour(double[], double[], double[][], double[]) - Constructor for class smile.plot.swing.Contour

Constructor.

Contour(double[], double[], double[][], int, boolean) - Constructor for class smile.plot.swing.Contour

Constructor.

conv2d(int, int, int) - Static method in interface smile.deep.layer.Layer

Returns a convolutional layer.

conv2d(int, int, int, int, int, int, int, boolean, String) - Static method in interface smile.deep.layer.Layer

Returns a convolutional layer.

conv2d(int, int, int, int, String, int, int, boolean, String) - Static method in interface smile.deep.layer.Layer

Returns a convolutional layer.

Conv2dLayer - Class in smile.deep.layer

A convolutional layer.

Conv2dLayer(int, int, int, int, int, int, int, boolean, String) - Constructor for class smile.deep.layer.Conv2dLayer

Constructor.

Conv2dLayer(int, int, int, int, String, int, int, boolean, String) - Constructor for class smile.deep.layer.Conv2dLayer

Constructor.

Conv2dNormActivation - Class in smile.vision.layer

Convolution2d-Normalization-Activation block.

Conv2dNormActivation(Conv2dNormActivation.Options) - Constructor for class smile.vision.layer.Conv2dNormActivation

Constructor.

Conv2dNormActivation.Options - Record Class in smile.vision.layer

Conv2dNormActivation configurations.

CooccurrenceKeywords - Interface in smile.nlp.keyword

Keyword extraction from a single document using word co-occurrence statistical information.

coordinates - Variable in class smile.manifold.IsoMap

The coordinate matrix in embedding space.

coordinates - Variable in class smile.manifold.IsotonicMDS

The coordinates.

coordinates - Variable in class smile.manifold.LaplacianEigenmap

The coordinate matrix in embedding space.

coordinates - Variable in class smile.manifold.LLE

The coordinate matrix in embedding space.

coordinates - Variable in class smile.manifold.MDS

The principal coordinates.

coordinates - Variable in class smile.manifold.SammonMapping

The coordinates.

coordinates - Variable in class smile.manifold.TSNE

The coordinate matrix in embedding space.

coordinates - Variable in class smile.manifold.UMAP

The coordinate matrix in embedding space.

coordinates() - Method in class smile.manifold.KPCA

Returns the nonlinear principal component scores, i.e., the representation of learning data in the nonlinear principal component space.

copy(double[][], double[][]) - Static method in class smile.math.MathEx

Deep copy x into y.

copy(float[][], float[][]) - Static method in class smile.math.MathEx

Deep copy x into y.

copy(int[][], int[][]) - Static method in class smile.math.MathEx

Copy x into y.

cor - Variable in class smile.stat.hypothesis.CorTest

The correlation coefficient.

cor(double[][]) - Static method in class smile.math.MathEx

Returns the sample correlation matrix.

cor(double[][], double[]) - Static method in class smile.math.MathEx

Returns the sample correlation matrix.

cor(double[][], String...) - Static method in class smile.feature.extraction.PCA

Fits principal component analysis with correlation matrix.

cor(double[], double[]) - Static method in class smile.math.MathEx

Returns the correlation coefficient between two vectors.

cor(float[], float[]) - Static method in class smile.math.MathEx

Returns the correlation coefficient between two vectors.

cor(int[], int[]) - Static method in class smile.math.MathEx

Returns the correlation coefficient between two vectors.

cor(DataFrame, String...) - Static method in class smile.feature.extraction.PCA

Fits principal component analysis with correlation matrix.

cornerRadius(double) - Method in class smile.plot.vega.Legend

Sets the corner radius for the full legend.

cornerRadius(double) - Method in class smile.plot.vega.Mark

Sets the radius in pixels of rounded rectangles or arcs' corners.

cornerRadius(int) - Method in class smile.plot.vega.Background

Sets the radius of corners.

cornerRadius(int) - Method in class smile.plot.vega.ViewConfig

Sets the radius of corners.

cornerRadiusBottomLeft(double) - Method in class smile.plot.vega.Mark

Sets the radius in pixels of rounded rectangles' bottom left corner.

cornerRadiusBottomRight(double) - Method in class smile.plot.vega.Mark

Sets the radius in pixels of rounded rectangles' bottom right corner.

cornerRadiusEnd(double) - Method in class smile.plot.vega.Mark

For vertical bars, sets the top-left and top-right corner radius.

cornerRadiusTopLeft(double) - Method in class smile.plot.vega.Mark

Sets the radius in pixels of rounded rectangles' top left corner.

cornerRadiusTopRight(double) - Method in class smile.plot.vega.Mark

Sets the radius in pixels of rounded rectangles' top right corner.

Corpus - Interface in smile.nlp

A corpus is a collection of documents.

CorrelationDistance - Class in smile.math.distance

Correlation distance is defined as 1 - correlation coefficient.

CorrelationDistance() - Constructor for class smile.math.distance.CorrelationDistance

Constructor of Pearson correlation distance.

CorrelationDistance(String) - Constructor for class smile.math.distance.CorrelationDistance

Constructor.

CorTest - Class in smile.stat.hypothesis

Correlation test.

CorTest(String, double, double, double, double) - Constructor for class smile.stat.hypothesis.CorTest

Constructor.

cos() - Method in class smile.deep.tensor.Tensor

Returns a new tensor with the cosine of the elements of input.

cos() - Method in class smile.math.Complex

Returns the complex cosine.

cos(double[], double[]) - Static method in class smile.math.MathEx

Returns the cosine similarity.

cos(float[], float[]) - Static method in class smile.math.MathEx

Returns the cosine similarity.

cos(String) - Static method in interface smile.data.formula.Terms

The cos(x) term.

cos(Term) - Static method in interface smile.data.formula.Terms

The cos(x) term.

cos_() - Method in class smile.deep.tensor.Tensor

Computes the cosine of the elements of input in place.

cosh(String) - Static method in interface smile.data.formula.Terms

The cosh(x) term.

cosh(Term) - Static method in interface smile.data.formula.Terms

The cosh(x) term.

cosine(double, double, double) - Static method in interface smile.math.TimeFunction

Returns the cosine annealing function.

cost() - Method in class smile.base.mlp.OutputLayer

Returns the cost function of neural network.

cost() - Method in class smile.manifold.TSNE

Returns the cost function value.

Cost - Enum Class in smile.base.mlp

Neural network cost function.

count - Variable in class smile.nlp.collocation.Bigram

The frequency of bigram in the corpus.

count - Variable in class smile.nlp.collocation.NGram

The frequency of n-gram in the corpus.

count() - Method in class smile.base.cart.DecisionNode

Returns the number of node samples in each class.

count(String) - Method in interface smile.nlp.Corpus

Returns the total frequency of the term in the corpus.

count(String) - Method in class smile.nlp.SimpleCorpus

count(Bigram) - Method in interface smile.nlp.Corpus

Returns the total frequency of the bigram in the corpus.

count(Bigram) - Method in class smile.nlp.SimpleCorpus

counter - Variable in class smile.vq.hebb.Neuron

The local counter variable (e.g.

counts(boolean) - Method in class smile.plot.vega.DensityTransform

Produces probability estimates or smoothed counts.

countTitle(String) - Method in class smile.plot.vega.Config

Sets the default axis and legend title for count fields.

cov - Variable in class smile.regression.GaussianProcessRegression.JointPrediction

The covariance matrix of joint predictive distribution at query points.

cov() - Method in interface smile.stat.distribution.MultivariateDistribution

The covariance matrix of distribution.

cov() - Method in class smile.stat.distribution.MultivariateGaussianDistribution

cov() - Method in class smile.stat.distribution.MultivariateMixture

cov(double[][]) - Static method in class smile.math.MathEx

Returns the sample covariance matrix.

cov(double[][], double[]) - Static method in class smile.math.MathEx

Returns the sample covariance matrix.

cov(double[], double[]) - Static method in class smile.math.MathEx

Returns the covariance between two vectors.

cov(double[], int) - Static method in interface smile.timeseries.TimeSeries

Autocovariance function.

cov(float[], float[]) - Static method in class smile.math.MathEx

Returns the covariance between two vectors.

cov(int[], int[]) - Static method in class smile.math.MathEx

Returns the covariance between two vectors.

CoverTree<K,V> - Class in smile.neighbor

Cover tree is a data structure for generic nearest neighbor search, which is especially efficient in spaces with small intrinsic dimension.

CoverTree(List<K>, List<V>, Metric<K>) - Constructor for class smile.neighbor.CoverTree

Constructor.

CoverTree(List<K>, List<V>, Metric<K>, double) - Constructor for class smile.neighbor.CoverTree

Constructor.

CoverTree(K[], V[], Metric<K>) - Constructor for class smile.neighbor.CoverTree

Constructor.

CoverTree(K[], V[], Metric<K>, double) - Constructor for class smile.neighbor.CoverTree

Constructor.

CPU - Enum constant in enum class smile.deep.tensor.DeviceType

CPU

CPU() - Static method in class smile.deep.tensor.Device

Returns the CPU device.

CramerV - Variable in class smile.stat.hypothesis.ChiSqTest

Cramér's V is a measure of association between two nominal variables, giving a value between 0 and 1 (inclusive).

CRF - Class in smile.sequence

First-order linear conditional random field.

CRF(StructType, RegressionTree[][], double) - Constructor for class smile.sequence.CRF

Constructor.

CRFLabeler<T> - Class in smile.sequence

First-order CRF sequence labeler.

CRFLabeler(CRF, Function<T, Tuple>) - Constructor for class smile.sequence.CRFLabeler

Constructor.

crop(BufferedImage, int, boolean) - Method in interface smile.vision.transform.Transform

Crops an image.

crop(BufferedImage, int, int, boolean) - Method in interface smile.vision.transform.Transform

Crops an image.

cross(int, String...) - Static method in interface smile.data.formula.Terms

Factor crossing of two or more factors.

cross(String...) - Static method in interface smile.data.formula.Terms

Factor crossing of two or more factors.

crossentropy - Variable in class smile.validation.ClassificationMetrics

The cross entropy on validation data.

crossEntropy() - Static method in interface smile.deep.Loss

Cross Entropy Loss Function.

CrossEntropy - Interface in smile.validation.metric

Cross entropy generalizes the log loss metric to multiclass problems.

crossover(Chromosome) - Method in class smile.gap.BitString

crossover(Chromosome) - Method in interface smile.gap.Chromosome

Returns a pair of offsprings by crossovering this one with another one according to the crossover rate, which determines how often will be crossover performed.

Crossover - Enum Class in smile.gap

The types of crossover operation.

CrossValidation - Interface in smile.validation

Cross-validation is a technique for assessing how the results of a statistical analysis will generalize to an independent data set.

csv(String) - Static method in interface smile.io.Read

Reads a CSV file.

csv(String, char, Map<String, String>, String...) - Method in class smile.data.SQL

Creates an in-memory table from csv files.

csv(String, String) - Static method in interface smile.io.Read

Reads a CSV file.

csv(String, String...) - Method in class smile.data.SQL

Creates an in-memory table from csv files.

csv(String, Map<String, String>) - Method in class smile.plot.vega.Data

Loads a comma-separated values (CSV) file

csv(String, CSVFormat) - Static method in interface smile.io.Read

Reads a CSV file.

csv(String, CSVFormat, StructType) - Static method in interface smile.io.Read

Reads a CSV file.

csv(Path) - Static method in interface smile.io.Read

Reads a CSV file.

csv(Path, CSVFormat) - Static method in interface smile.io.Read

Reads a CSV file.

csv(Path, CSVFormat, StructType) - Static method in interface smile.io.Read

Reads a CSV file.

csv(DataFrame, Path) - Static method in interface smile.io.Write

Writes a CSV file.

csv(DataFrame, Path, CSVFormat) - Static method in interface smile.io.Write

Writes a CSV file.

CSV - Class in smile.io

Reads and writes files in variations of the Comma Separated Value (CSV) format.

CSV() - Constructor for class smile.io.CSV

Constructor.

CSV(CSVFormat) - Constructor for class smile.io.CSV

Constructor.

CubicSplineInterpolation1D - Class in smile.interpolation

Cubic spline interpolation.

CubicSplineInterpolation1D(double[], double[]) - Constructor for class smile.interpolation.CubicSplineInterpolation1D

Constructor.

CubicSplineInterpolation2D - Class in smile.interpolation

Cubic spline interpolation in a two-dimensional regular grid.

CubicSplineInterpolation2D(double[], double[], double[][]) - Constructor for class smile.interpolation.CubicSplineInterpolation2D

Constructor.

CUDA - Enum constant in enum class smile.deep.tensor.DeviceType

NVIDIA GPU

CUDA - Interface in smile.deep

NVIDIA CUDA helper functions.

CUDA() - Static method in class smile.deep.tensor.Device

Returns the default NVIDIA CUDA device.

CUDA(byte) - Static method in class smile.deep.tensor.Device

Returns the NVIDIA CUDA device.

cumulative(boolean) - Method in class smile.plot.vega.DensityTransform

Produces density estimates or cumulative density estimates.

cumulativeVarianceProportion() - Method in class smile.feature.extraction.PCA

Returns the cumulative proportion of variance contained in principal components, ordered from largest to smallest.

Currency - Static variable in interface smile.data.measure.Measure

Currency.

CURRENCY - Static variable in class smile.swing.table.NumberCellRenderer

cursor(String) - Method in class smile.plot.vega.Background

Sets the mouse cursor used over the view.

cursor(String) - Method in class smile.plot.vega.ViewConfig

Sets the mouse cursor used over the view.

customFormatTypes(boolean) - Method in class smile.plot.vega.FormatConfig

Allow the formatType property for text marks and guides to accept a custom formatter function registered as a Vega expression.

CYAN - Static variable in interface smile.plot.swing.Palette

D

d - Variable in class smile.stat.hypothesis.KSTest

Kolmogorov-Smirnov statistic.

d - Variable in class smile.vq.BIRCH

The dimensionality of data.

d(byte[], byte[]) - Static method in class smile.math.distance.HammingDistance

Returns Hamming distance between the two byte arrays.

d(byte, byte) - Static method in class smile.math.distance.HammingDistance

Returns Hamming distance between the two bytes.

d(char[], char[]) - Method in class smile.math.distance.EditDistance

Edit distance between two strings.

d(double[], double[]) - Method in class smile.math.distance.ChebyshevDistance

Chebyshev distance between the two arrays of type double.

d(double[], double[]) - Method in class smile.math.distance.CorrelationDistance

Pearson correlation distance between the two arrays of type double.

d(double[], double[]) - Static method in class smile.math.distance.DynamicTimeWarping

Dynamic time warping without path constraints.

d(double[], double[]) - Method in class smile.math.distance.EuclideanDistance

Euclidean distance between the two arrays of type double.

d(double[], double[]) - Method in class smile.math.distance.JensenShannonDistance

d(double[], double[]) - Method in class smile.math.distance.MahalanobisDistance

d(double[], double[]) - Method in class smile.math.distance.ManhattanDistance

Manhattan distance between two arrays of type double.

d(double[], double[]) - Method in class smile.math.distance.MinkowskiDistance

Minkowski distance between the two arrays of type double.

d(double[], double[], int) - Static method in class smile.math.distance.DynamicTimeWarping

Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.

d(float[], float[]) - Static method in class smile.math.distance.ChebyshevDistance

Chebyshev distance between the two arrays of type float.

d(float[], float[]) - Static method in class smile.math.distance.DynamicTimeWarping

Dynamic time warping without path constraints.

d(float[], float[]) - Method in class smile.math.distance.EuclideanDistance

Euclidean distance between the two arrays of type float.

d(float[], float[]) - Method in class smile.math.distance.ManhattanDistance

Manhattan distance between two arrays of type float.

d(float[], float[]) - Method in class smile.math.distance.MinkowskiDistance

Minkowski distance between the two arrays of type float.

d(float[], float[], int) - Static method in class smile.math.distance.DynamicTimeWarping

Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.

d(int[], int[]) - Static method in class smile.math.distance.ChebyshevDistance

Chebyshev distance between the two arrays of type integer.

d(int[], int[]) - Static method in class smile.math.distance.DynamicTimeWarping

Dynamic time warping without path constraints.

d(int[], int[]) - Method in class smile.math.distance.EuclideanDistance

Euclidean distance between the two arrays of type integer.

d(int[], int[]) - Static method in class smile.math.distance.HammingDistance

Returns Hamming distance between the two integer arrays.

d(int[], int[]) - Method in class smile.math.distance.LeeDistance

d(int[], int[]) - Method in class smile.math.distance.ManhattanDistance

Manhattan distance between two arrays of type integer.

d(int[], int[]) - Method in class smile.math.distance.MinkowskiDistance

Minkowski distance between the two arrays of type integer.

d(int[], int[], int) - Static method in class smile.math.distance.DynamicTimeWarping

Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.

d(int, int) - Method in class smile.clustering.linkage.Linkage

Returns the distance/dissimilarity between two clusters/objects, which are indexed by integers.

d(int, int) - Static method in class smile.math.distance.HammingDistance

Returns Hamming distance between the two integers.

d(long, long) - Static method in class smile.math.distance.HammingDistance

Returns Hamming distance between the two long integers.

d(short[], short[]) - Static method in class smile.math.distance.HammingDistance

Returns Hamming distance between the two short arrays.

d(short, short) - Static method in class smile.math.distance.HammingDistance

Returns Hamming distance between the two shorts.

d(String, String) - Method in class smile.math.distance.EditDistance

Edit distance between two strings.

d(String, String) - Method in class smile.taxonomy.TaxonomicDistance

Computes the distance between two concepts in a taxonomy.

d(BitSet, BitSet) - Method in class smile.math.distance.HammingDistance

d(Set<T>, Set<T>) - Static method in class smile.math.distance.JaccardDistance

Returns the Jaccard distance between sets.

d(Concept, Concept) - Method in class smile.taxonomy.TaxonomicDistance

Computes the distance between two concepts in a taxonomy.

d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseChebyshevDistance

d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseEuclideanDistance

d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseManhattanDistance

d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseMinkowskiDistance

d(T[], T[]) - Method in class smile.math.distance.DynamicTimeWarping

d(T[], T[]) - Method in class smile.math.distance.JaccardDistance

d(T, T) - Method in interface smile.math.distance.Distance

Returns the distance measure between two objects.

D(T[]) - Method in interface smile.math.distance.Distance

Returns the pairwise distance matrix.

D(T[], T[]) - Method in interface smile.math.distance.Distance

Returns the pairwise distance matrix.

D4Wavelet - Class in smile.wavelet

The simplest and most localized wavelet, Daubechies wavelet of 4 coefficients.

D4Wavelet() - Constructor for class smile.wavelet.D4Wavelet

Constructor.

damerau(char[], char[]) - Static method in class smile.math.distance.EditDistance

Damerau-Levenshtein distance between two strings allows insertion, deletion, substitution, or transposition of characters.

damerau(String, String) - Static method in class smile.math.distance.EditDistance

Damerau-Levenshtein distance between two strings allows insertion, deletion, substitution, or transposition of characters.

DARK_BLUE - Static variable in interface smile.plot.swing.Palette

DARK_CYAN - Static variable in interface smile.plot.swing.Palette

DARK_GRAY - Static variable in interface smile.plot.swing.Palette

DARK_GREEN - Static variable in interface smile.plot.swing.Palette

DARK_MAGENTA - Static variable in interface smile.plot.swing.Palette

DARK_PURPLE - Static variable in interface smile.plot.swing.Palette

DARK_RED - Static variable in interface smile.plot.swing.Palette

DARK_SLATE_GRAY - Static variable in interface smile.plot.swing.Palette

DASH - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Punctuation -

DASH - Enum constant in enum class smile.plot.swing.Line.Style

data - Variable in class smile.neighbor.LSH

The data objects.

data() - Method in record class smile.deep.SampleBatch

Returns the value of the data record component.

data() - Method in class smile.plot.vega.LookupData

Returns the secondary data source.

data() - Method in class smile.plot.vega.VegaLite

Returns the data specification object.

data(String) - Static method in interface smile.io.Read

Reads a data file.

data(String, String) - Static method in interface smile.io.Read

Reads a data file.

Data - Class in smile.plot.vega

The basic data model used by Vega-Lite is tabular data.

DataFrame - Interface in smile.data

An immutable collection of data organized into named columns.

DataFrame.Collectors - Interface in smile.data

Stream collectors.

DataFrameClassifier - Interface in smile.classification

Classification trait on DataFrame.

DataFrameClassifier.Trainer<M> - Interface in smile.classification

The classifier trainer.

DataFrameRegression - Interface in smile.regression

Regression trait on DataFrame.

DataFrameRegression.Trainer<M> - Interface in smile.regression

The regression trainer.

Dataset<D,T> - Interface in smile.data

An immutable collection of data objects.

Dataset - Interface in smile.deep

A dataset consists of data and an associated target (label) and can be iterated in mini-batches.

DataType - Interface in smile.data.type

The interface of data types.

DataType.ID - Enum Class in smile.data.type

Data type ID.

DataTypes - Class in smile.data.type

To get a specific data type, users should use singleton objects and factory methods in this class.

DataTypes() - Constructor for class smile.data.type.DataTypes

date(String) - Static method in class smile.data.type.DataTypes

Date data type with customized format.

date(String, DateFeature...) - Static method in interface smile.data.formula.Terms

Extracts date/time features.

Date - Class in smile.data.formula

Date/time feature extractor.

Date - Enum constant in enum class smile.data.type.DataType.ID

Date type ID.

Date(String, DateFeature...) - Constructor for class smile.data.formula.Date

Constructor.

DATE - Static variable in interface smile.util.Regex

Date regular expression pattern.

DateCellEditor - Class in smile.swing.table

Implements a cell editor that uses a formatted text field to edit Date values.

DateCellEditor(String) - Constructor for class smile.swing.table.DateCellEditor

Constructor.

DateCellEditor(DateFormat) - Constructor for class smile.swing.table.DateCellEditor

Constructor.

DateCellRenderer - Class in smile.swing.table

Date cell renderer.

DateCellRenderer(String) - Constructor for class smile.swing.table.DateCellRenderer

DateCellRenderer(DateFormat) - Constructor for class smile.swing.table.DateCellRenderer

DateFeature - Enum Class in smile.data.formula

The date/time features.

datetime(String) - Static method in class smile.data.type.DataTypes

DateTime data type with customized format.

DateTime - Enum constant in enum class smile.data.type.DataType.ID

DateTime type ID.

DATETIME - Static variable in interface smile.util.Regex

Datetime regular expression pattern.

DateTimeType - Class in smile.data.type

DateTime data type.

DateTimeType - Static variable in class smile.data.type.DataTypes

DateTime data type with ISO format.

DateTimeType(String) - Constructor for class smile.data.type.DateTimeType

Constructor.

DateType - Class in smile.data.type

Date data type.

DateType - Static variable in class smile.data.type.DataTypes

Date data type with ISO format.

DateType(String) - Constructor for class smile.data.type.DateType

Constructor.

DaubechiesWavelet - Class in smile.wavelet

Daubechies wavelets.

DaubechiesWavelet(int) - Constructor for class smile.wavelet.DaubechiesWavelet

Constructor.

DAY_OF_MONTH - Enum constant in enum class smile.data.formula.DateFeature

The day of month represented by an integer from 1 to 31 in the usual manner.

DAY_OF_WEEK - Enum constant in enum class smile.data.formula.DateFeature

The day of week represented by an integer from 1 to 7; 1 is Monday, 2 is Tuesday, and so forth; thus 7 is Sunday.

DAY_OF_YEAR - Enum constant in enum class smile.data.formula.DateFeature

The day of year represented by an integer from 1 to 365, or 366 in a leap year.

DBSCAN<T> - Class in smile.clustering

Density-Based Spatial Clustering of Applications with Noise.

DBSCAN(int, double, RNNSearch<T, T>, int, int[], boolean[]) - Constructor for class smile.clustering.DBSCAN

Constructor.

Decimal - Enum constant in enum class smile.data.type.DataType.ID

Decimal type ID.

DECIMAL_FORMAT - Static variable in interface smile.util.Strings

Decimal format for floating numbers.

DecimalType - Class in smile.data.type

Arbitrary-precision decimal data type.

DecimalType - Static variable in class smile.data.type.DataTypes

Decimal data type.

DecisionNode - Class in smile.base.cart

A leaf node in decision tree.

DecisionNode(int[]) - Constructor for class smile.base.cart.DecisionNode

Constructor.

DecisionTree - Class in smile.classification

Decision tree.

DecisionTree(DataFrame, int[], StructField, int, SplitRule, int, int, int, int, int[], int[][]) - Constructor for class smile.classification.DecisionTree

Constructor.

decode(int[]) - Method in class smile.llm.tokenizer.SentencePiece

decode(int[]) - Method in class smile.llm.tokenizer.Tiktoken

decode(int[]) - Method in interface smile.llm.tokenizer.Tokenizer

Decodes a list of token IDs into a string.

decrement() - Method in class smile.util.MutableInt

Decrement by one.

decrement(int) - Method in class smile.util.MutableInt

Decrement.

DEFAULT - Enum constant in enum class smile.nlp.dictionary.EnglishStopWords

Default stop words list.

DEFAULT_MEAN - Static variable in interface smile.vision.transform.Transform

The default mean value of pixel RGB after normalized to [0, 1].

DEFAULT_STD - Static variable in interface smile.vision.transform.Transform

The default standard deviation of pixel RGB after normalized to [0, 1].

DefaultTableHeaderCellRenderer - Class in smile.swing.table

A default cell renderer for a JTableHeader.

DefaultTableHeaderCellRenderer() - Constructor for class smile.swing.table.DefaultTableHeaderCellRenderer

Constructs a DefaultTableHeaderCellRenderer.

degree() - Method in class smile.math.kernel.Polynomial

Returns the degree of polynomial.

delete(String) - Static method in interface smile.data.formula.Terms

Deletes a variable or the intercept ("1") from the formula.

delete(Term) - Static method in interface smile.data.formula.Terms

Deletes a term from the formula.

DENCLUE - Class in smile.clustering

DENsity CLUstering.

DENCLUE(int, double[][], double[], double[][], double, int[], double) - Constructor for class smile.clustering.DENCLUE

Constructor.

Dendrogram - Class in smile.plot.swing

A dendrogram is a tree diagram frequently used to illustrate the arrangement of the clusters produced by hierarchical clustering.

Dendrogram(int[][], double[]) - Constructor for class smile.plot.swing.Dendrogram

Constructor.

Dendrogram(int[][], double[], Color) - Constructor for class smile.plot.swing.Dendrogram

Constructor.

denoise(double[], Wavelet) - Static method in interface smile.wavelet.WaveletShrinkage

Adaptive hard-thresholding denoising a time series with given wavelet.

denoise(double[], Wavelet, boolean) - Static method in interface smile.wavelet.WaveletShrinkage

Adaptive denoising a time series with given wavelet.

density(String, String...) - Method in class smile.plot.vega.Transform

Adds a density transformation.

DensityTransform - Class in smile.plot.vega

The density transform performs one-dimensional kernel density estimation over an input data stream and generates a new data stream of samples of the estimated densities.

depth() - Method in class smile.base.cart.InternalNode

depth() - Method in class smile.base.cart.LeafNode

depth() - Method in interface smile.base.cart.Node

Returns the maximum depth of the tree -- the number of nodes along the longest path from this node down to the farthest leaf node.

describe(String) - Method in class smile.data.SQL

Returns the columns in a table.

description(String) - Method in class smile.plot.vega.Axis

Sets the text description of this axis for ARIA accessibility (SVG output only).

description(String) - Method in class smile.plot.vega.Concat

description(String) - Method in class smile.plot.vega.Facet

description(String) - Method in class smile.plot.vega.Legend

Sets the text description of this legend for ARIA accessibility (SVG output only).

description(String) - Method in class smile.plot.vega.Mark

Sets the description.

description(String) - Method in class smile.plot.vega.Repeat

description(String) - Method in class smile.plot.vega.VegaLite

Sets the description of this mark for commenting purpose.

description(String) - Method in class smile.plot.vega.View

det() - Method in class smile.math.matrix.BandMatrix.Cholesky

Returns the matrix determinant.

det() - Method in class smile.math.matrix.BandMatrix.LU

Returns the matrix determinant.

det() - Method in class smile.math.matrix.BigMatrix.Cholesky

Returns the matrix determinant.

det() - Method in class smile.math.matrix.BigMatrix.LU

Returns the matrix determinant.

det() - Method in class smile.math.matrix.fp32.BandMatrix.Cholesky

Returns the matrix determinant.

det() - Method in class smile.math.matrix.fp32.BandMatrix.LU

Returns the matrix determinant.

det() - Method in class smile.math.matrix.fp32.Matrix.Cholesky

Returns the matrix determinant.

det() - Method in class smile.math.matrix.fp32.Matrix.LU

Returns the matrix determinant.

det() - Method in class smile.math.matrix.fp32.SymmMatrix.BunchKaufman

Returns the matrix determinant.

det() - Method in class smile.math.matrix.fp32.SymmMatrix.Cholesky

Returns the matrix determinant.

det() - Method in class smile.math.matrix.Matrix.Cholesky

Returns the matrix determinant.

det() - Method in class smile.math.matrix.Matrix.LU

Returns the matrix determinant.

det() - Method in class smile.math.matrix.SymmMatrix.BunchKaufman

Returns the matrix determinant.

det() - Method in class smile.math.matrix.SymmMatrix.Cholesky

Returns the matrix determinant.

detach() - Method in class smile.deep.tensor.Tensor

Returns a new tensor, detached from the current graph.

detach(AutoCloseable...) - Method in class smile.util.AutoScope

Detaches resources from this Scope.

DeterministicAnnealing - Class in smile.clustering

Deterministic annealing clustering.

DeterministicAnnealing(double, double[][], int[]) - Constructor for class smile.clustering.DeterministicAnnealing

Constructor.

deviance - Variable in class smile.glm.GLM

The deviance = 2 * (LogLikelihood(Saturated Model) - LogLikelihood(Proposed Model)).

deviance() - Method in class smile.base.cart.DecisionNode

deviance() - Method in class smile.base.cart.InternalNode

deviance() - Method in interface smile.base.cart.Node

Returns the deviance of node.

deviance() - Method in class smile.base.cart.RegressionNode

deviance() - Method in class smile.glm.GLM

Returns the deviance of model.

deviance(double[], double[], double[]) - Method in interface smile.glm.model.Model

The deviance function.

deviance(int[], double[]) - Static method in class smile.base.cart.DecisionNode

Returns the deviance of node.

devianceResiduals - Variable in class smile.glm.GLM

The deviance residuals.

devianceResiduals() - Method in class smile.glm.GLM

Returns the deviance residuals.

device() - Static method in interface smile.deep.CUDA

Returns the default CUDA device.

device() - Method in class smile.deep.Model

Returns the device on which the model is stored.

device() - Method in class smile.deep.tensor.Tensor

Returns the device on which the tensor is.

device(byte) - Static method in interface smile.deep.CUDA

Returns the CUDA device of given index.

device(Device) - Method in class smile.deep.tensor.Tensor.Options

Sets a compute device on which a tensor is stored.

Device - Class in smile.deep.tensor

The compute device on which a tensor is stored.

Device(DeviceType) - Constructor for class smile.deep.tensor.Device

Constructor.

Device(DeviceType, byte) - Constructor for class smile.deep.tensor.Device

Constructor.

deviceCount() - Static method in interface smile.deep.CUDA

Returns the number of CUDA devices.

DeviceType - Enum Class in smile.deep.tensor

The compute device type.

df - Variable in class smile.glm.GLM

The degrees of freedom of the residual deviance.

df - Variable in class smile.stat.hypothesis.ChiSqTest

The degree of freedom of chi-square statistic.

df - Variable in class smile.stat.hypothesis.CorTest

The degree of freedom of test statistic.

df - Variable in class smile.stat.hypothesis.TTest

The degree of freedom of t-statistic.

df - Variable in class smile.timeseries.BoxTest

The degree of freedom.

df() - Method in class smile.regression.LinearModel

Returns the degree-of-freedom of residual standard error.

df() - Method in class smile.timeseries.AR

Returns the degree-of-freedom of residual standard error.

df() - Method in class smile.timeseries.ARMA

Returns the degree-of-freedom of residual standard error.

df1 - Variable in class smile.stat.hypothesis.FTest

The degree of freedom of F-statistic.

df2 - Variable in class smile.stat.hypothesis.FTest

The degree of freedom of F-statistic.

dfs() - Method in class smile.graph.AdjacencyList

dfs() - Method in class smile.graph.AdjacencyMatrix

dfs() - Method in interface smile.graph.Graph

Depth-first search connected components of graph.

dfs(Visitor) - Method in class smile.graph.AdjacencyList

dfs(Visitor) - Method in class smile.graph.AdjacencyMatrix

dfs(Visitor) - Method in interface smile.graph.Graph

DFS search on graph and performs some operation defined in visitor on each vertex during traveling.

diag() - Method in class smile.math.matrix.BigMatrix.EVD

Returns the block diagonal eigenvalue matrix whose diagonal are the real part of eigenvalues, lower subdiagonal are positive imaginary parts, and upper subdiagonal are negative imaginary parts.

diag() - Method in class smile.math.matrix.BigMatrix.SVD

Returns the diagonal matrix of singular values.

diag() - Method in class smile.math.matrix.fp32.IMatrix

Returns the diagonal elements.

diag() - Method in class smile.math.matrix.fp32.Matrix.EVD

Returns the block diagonal eigenvalue matrix whose diagonal are the real part of eigenvalues, lower subdiagonal are positive imaginary parts, and upper subdiagonal are negative imaginary parts.

diag() - Method in class smile.math.matrix.fp32.Matrix.SVD

Returns the diagonal matrix of singular values.

diag() - Method in class smile.math.matrix.fp32.SparseMatrix

diag() - Method in class smile.math.matrix.IMatrix

Returns the diagonal elements.

diag() - Method in class smile.math.matrix.Matrix.EVD

Returns the block diagonal eigenvalue matrix whose diagonal are the real part of eigenvalues, lower subdiagonal are positive imaginary parts, and upper subdiagonal are negative imaginary parts.

diag() - Method in class smile.math.matrix.Matrix.SVD

Returns the diagonal matrix of singular values.

diag() - Method in class smile.math.matrix.SparseMatrix

diag(double[]) - Static method in class smile.math.matrix.BigMatrix

Returns a square diagonal matrix.

diag(double[]) - Static method in class smile.math.matrix.Matrix

Returns a square diagonal matrix.

diag(float[]) - Static method in class smile.math.matrix.fp32.Matrix

Returns a square diagonal matrix.

diag(int, double) - Static method in class smile.math.matrix.BigMatrix

Returns a square diagonal matrix.

diag(int, double) - Static method in class smile.math.matrix.Matrix

Returns a square diagonal matrix.

diag(int, float) - Static method in class smile.math.matrix.fp32.Matrix

Returns a square diagonal matrix.

diag(int, int, double) - Static method in class smile.math.matrix.BigMatrix

Returns an m-by-n diagonal matrix.

diag(int, int, double) - Static method in class smile.math.matrix.Matrix

Returns an m-by-n diagonal matrix.

diag(int, int, float) - Static method in class smile.math.matrix.fp32.Matrix

Returns an m-by-n diagonal matrix.

diag(DoublePointer) - Static method in class smile.math.matrix.BigMatrix

Returns a square diagonal matrix.

Diag - Enum Class in smile.math.blas

The flag if a triangular matrix has unit diagonal elements.

diagonal - Variable in class smile.stat.distribution.MultivariateGaussianDistribution

True if the covariance matrix is diagonal.

dialogResultValue - Variable in class smile.swing.FontChooser

Dictionary - Interface in smile.nlp.dictionary

A dictionary is a set of words in some natural language.

diff(double[], int) - Static method in interface smile.timeseries.TimeSeries

Returns the first-differencing of time series.

diff(double[], int, int) - Static method in interface smile.timeseries.TimeSeries

Returns the differencing of time series.

DifferentiableFunction - Interface in smile.math

A differentiable function is a function whose derivative exists at each point in its domain.

DifferentiableMultivariateFunction - Interface in smile.math

A differentiable function is a function whose derivative exists at each point in its domain.

digamma(double) - Static method in class smile.math.special.Gamma

The digamma function is defined as the logarithmic derivative of the gamma function.

DIGITS - Static variable in class smile.math.MathEx

The number of digits (in radix base) in the mantissa.

dijkstra() - Method in interface smile.graph.Graph

Calculates the all pair shortest path by Dijkstra algorithm.

dijkstra(int) - Method in class smile.graph.AdjacencyList

dijkstra(int) - Method in class smile.graph.AdjacencyMatrix

dijkstra(int) - Method in interface smile.graph.Graph

Calculate the shortest path from a source to all other vertices in the graph by Dijkstra algorithm.

dijkstra(int, boolean) - Method in class smile.graph.AdjacencyMatrix

Calculates the shortest path by Dijkstra algorithm.

dilation() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns the value of the dilation record component.

dim() - Method in class smile.deep.tensor.Tensor

Returns the number of dimensions of tensor.

dimension() - Method in class smile.classification.Maxent

Returns the dimension of input space.

dimension() - Method in class smile.nlp.embedding.Word2Vec

Returns the dimension of embedding vector space.

dimFeedForward() - Method in record class smile.llm.Transformer.Options

Returns the value of the dimFeedForward record component.

dir() - Static method in interface smile.util.CacheFiles

Returns the cache directory path.

direction(String) - Method in class smile.plot.vega.Legend

Sets the direction of the legend, one of "vertical" or "horizontal".

DiscreteDistribution - Class in smile.stat.distribution

Univariate discrete distributions.

DiscreteDistribution() - Constructor for class smile.stat.distribution.DiscreteDistribution

DiscreteExponentialFamily - Interface in smile.stat.distribution

The purpose of this interface is mainly to define the method M that is the Maximization step in the EM algorithm.

DiscreteExponentialFamilyMixture - Class in smile.stat.distribution

The finite mixture of distributions from discrete exponential family.

DiscreteExponentialFamilyMixture(DiscreteMixture.Component...) - Constructor for class smile.stat.distribution.DiscreteExponentialFamilyMixture

Constructor.

discreteHeight(int) - Method in class smile.plot.vega.ViewConfig

Sets the default height when the plot has non arc marks and either a discrete y-field or no y-field.

DiscreteMixture - Class in smile.stat.distribution

The finite mixture of discrete distributions.

DiscreteMixture(DiscreteMixture.Component...) - Constructor for class smile.stat.distribution.DiscreteMixture

Constructor.

DiscreteMixture.Component - Class in smile.stat.distribution

A component in the mixture distribution is defined by a distribution and its weight in the mixture.

DiscreteNaiveBayes - Class in smile.classification

Naive Bayes classifier for document classification in NLP.

DiscreteNaiveBayes(DiscreteNaiveBayes.Model, double[], int) - Constructor for class smile.classification.DiscreteNaiveBayes

Constructor of naive Bayes classifier for document classification.

DiscreteNaiveBayes(DiscreteNaiveBayes.Model, double[], int, double, IntSet) - Constructor for class smile.classification.DiscreteNaiveBayes

Constructor of naive Bayes classifier for document classification.

DiscreteNaiveBayes(DiscreteNaiveBayes.Model, int, int) - Constructor for class smile.classification.DiscreteNaiveBayes

Constructor of naive Bayes classifier for document classification.

DiscreteNaiveBayes(DiscreteNaiveBayes.Model, int, int, double, IntSet) - Constructor for class smile.classification.DiscreteNaiveBayes

Constructor of naive Bayes classifier for document classification.

DiscreteNaiveBayes.Model - Enum Class in smile.classification

The generation models of naive Bayes classifier.

discreteWidth(int) - Method in class smile.plot.vega.ViewConfig

Sets the default width when the plot has non-arc marks and either a discrete x-field or no x-field.

distance - Variable in class smile.neighbor.Neighbor

The distance between the query and the neighbor.

distance - Variable in class smile.vq.hebb.Neuron

The distance between the neuron and an input signal.

distance(double[]) - Method in class smile.vq.hebb.Neuron

Computes the distance between the neuron and a signal.

distance(double[], double[]) - Method in class smile.clustering.DeterministicAnnealing

distance(double[], double[]) - Method in class smile.clustering.GMeans

distance(double[], double[]) - Method in class smile.clustering.KMeans

distance(double[], double[]) - Method in class smile.clustering.XMeans

distance(double[], double[]) - Static method in class smile.math.MathEx

The Euclidean distance.

distance(double[], SparseArray) - Method in class smile.clustering.SIB

distance(float[], float[]) - Static method in class smile.math.MathEx

The Euclidean distance.

distance(int[], int[]) - Method in class smile.clustering.KModes

distance(int[], int[]) - Static method in class smile.math.MathEx

The Euclidean distance on binary sparse arrays, which are the indices of nonzero elements in ascending order.

distance(SparseArray, SparseArray) - Static method in class smile.math.MathEx

The Euclidean distance.

distance(T, T) - Method in class smile.clustering.CLARANS

distance(T, U) - Method in class smile.clustering.CentroidClustering

The distance function.

Distance<T> - Interface in smile.math.distance

An interface to calculate a distance measure between two objects.

distinct() - Method in interface smile.data.vector.Vector

Returns the distinct values.

distortion - Variable in class smile.clustering.CentroidClustering

The total distortion.

distortion - Variable in class smile.clustering.SpectralClustering

The distortion in feature space.

distribution - Variable in class smile.stat.distribution.DiscreteMixture.Component

The distribution of component.

distribution - Variable in class smile.stat.distribution.Mixture.Component

The distribution of component.

distribution - Variable in class smile.stat.distribution.MultivariateMixture.Component

The distribution of component.

Distribution - Interface in smile.stat.distribution

Probability distribution of univariate random variable.

div(double) - Method in class smile.deep.tensor.Tensor

Returns A / b.

div(double) - Method in class smile.math.matrix.BigMatrix

A /= b

div(double) - Method in class smile.math.matrix.Matrix

A /= b

div(double) - Method in class smile.util.Array2D

A /= x.

div(float) - Method in class smile.deep.tensor.Tensor

Returns A / b.

div(float) - Method in class smile.math.matrix.fp32.Matrix

A /= b

div(int) - Method in class smile.util.IntArray2D

A /= x.

div(int, int, double) - Method in class smile.math.matrix.BigMatrix

A[i,j] /= b

div(int, int, double) - Method in class smile.math.matrix.Matrix

A[i,j] /= b

div(int, int, double) - Method in class smile.util.Array2D

A[i, j] /= x.

div(int, int, float) - Method in class smile.math.matrix.fp32.Matrix

A[i,j] /= b

div(int, int, int) - Method in class smile.util.IntArray2D

A[i, j] /= x.

div(String, String) - Static method in interface smile.data.formula.Terms

Divides two terms.

div(String, Term) - Static method in interface smile.data.formula.Terms

Divides two terms.

div(Term, String) - Static method in interface smile.data.formula.Terms

Divides two terms.

div(Term, Term) - Static method in interface smile.data.formula.Terms

Divides two terms.

div(Tensor) - Method in class smile.deep.tensor.Tensor

Returns A / B element wisely.

div(Complex) - Method in class smile.math.Complex

Returns a / b.

div(BigMatrix) - Method in class smile.math.matrix.BigMatrix

Element-wise division A /= B

div(Matrix) - Method in class smile.math.matrix.fp32.Matrix

Element-wise division A /= B

div(Matrix) - Method in class smile.math.matrix.Matrix

Element-wise division A /= B

div(Array2D) - Method in class smile.util.Array2D

A /= B.

div(IntArray2D) - Method in class smile.util.IntArray2D

A /= B.

Div - Class in smile.data.formula

The term of a / b expression.

Div(Term, Term) - Constructor for class smile.data.formula.Div

Constructor.

div_(double) - Method in class smile.deep.tensor.Tensor

Returns A /= b.

div_(float) - Method in class smile.deep.tensor.Tensor

Returns A /= b.

div_(Tensor) - Method in class smile.deep.tensor.Tensor

Returns A /= B element wisely.

divide(int...) - Method in class smile.plot.vega.BinParams

Sets the scale factors indicating allowable subdivisions.

dlink(double) - Method in interface smile.glm.model.Model

The derivative of link function.

dModel() - Method in record class smile.llm.Transformer.Options

Returns the value of the dModel record component.

domain(boolean) - Method in class smile.plot.vega.Axis

Sets if the domain (the axis baseline) should be included as part of the axis.

domain(double...) - Method in class smile.plot.vega.Field

Sets the customize domain values.

domain(String...) - Method in class smile.plot.vega.Field

Sets the customize domain values.

domainCap(String) - Method in class smile.plot.vega.Axis

Sets the stroke cap for the domain line's ending style.

domainColor(String) - Method in class smile.plot.vega.Axis

Sets the color of axis domain line.

domainDash(double, double) - Method in class smile.plot.vega.Axis

Sets the alternating [stroke, space] lengths for dashed domain lines.

domainDashOffset(double) - Method in class smile.plot.vega.Axis

Sets the pixel offset at which to start drawing with the domain dash array.

domainMax(double) - Method in class smile.plot.vega.Field

Sets the maximum value in the scale domain, overriding the domain property or the default domain.

domainMax(String) - Method in class smile.plot.vega.Field

Sets the maximum value in the scale domain, overriding the domain property or the default domain.

domainMin(double) - Method in class smile.plot.vega.Field

Sets the minimum value in the scale domain, overriding the domain property or the default domain.

domainMin(String) - Method in class smile.plot.vega.Field

Sets the minimum value in the scale domain, overriding the domain property or the default domain.

domainOpacity(double) - Method in class smile.plot.vega.Axis

Sets the opacity of the axis domain line.

domainWidth(double) - Method in class smile.plot.vega.Axis

Sets the stroke width of axis domain line.

dot() - Method in class smile.base.cart.CART

Returns the graphic representation in Graphviz dot format.

dot() - Static method in interface smile.data.formula.Terms

Returns the special term "." that means all columns not otherwise in the formula in the context of a data frame.

dot(double[], double[]) - Method in interface smile.math.blas.BLAS

Computes the dot product of two vectors.

dot(double[], double[]) - Static method in class smile.math.MathEx

Returns the dot product between two vectors.

dot(float[], float[]) - Method in interface smile.math.blas.BLAS

Computes the dot product of two vectors.

dot(float[], float[]) - Static method in class smile.math.MathEx

Returns the dot product between two vectors.

dot(int[], int[]) - Static method in class smile.math.MathEx

Returns the dot product between two binary sparse arrays, which are the indices of nonzero elements in ascending order.

dot(int, double[], int, double[], int) - Method in interface smile.math.blas.BLAS

Computes the dot product of two vectors.

dot(int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

dot(int, float[], int, float[], int) - Method in interface smile.math.blas.BLAS

Computes the dot product of two vectors.

dot(int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

dot(StructType, StructField, int) - Method in class smile.base.cart.DecisionNode

dot(StructType, StructField, int) - Method in interface smile.base.cart.Node

Returns the dot representation of node.

dot(StructType, StructField, int) - Method in class smile.base.cart.NominalNode

dot(StructType, StructField, int) - Method in class smile.base.cart.OrdinalNode

dot(StructType, StructField, int) - Method in class smile.base.cart.RegressionNode

dot(SparseArray, SparseArray) - Static method in class smile.math.MathEx

Returns the dot product between two sparse arrays.

DOT - Enum constant in enum class smile.plot.swing.Line.Style

DOT_DASH - Enum constant in enum class smile.plot.swing.Line.Style

DotProductKernel - Interface in smile.math.kernel

Dot product kernel depends only on the dot product of x and y.

Double - Enum constant in enum class smile.data.type.DataType.ID

Double type ID.

DOUBLE - Static variable in interface smile.util.Regex

Double regular expression pattern.

DOUBLE_REGEX - Static variable in interface smile.util.Regex

Double regular expression.

DoubleArrayCellEditor - Class in smile.swing.table

Implements a cell editor that uses a formatted text field to edit double[] values.

DoubleArrayCellEditor() - Constructor for class smile.swing.table.DoubleArrayCellEditor

Constructor.

DoubleArrayCellRenderer - Class in smile.swing.table

Double array renderer in JTable.

DoubleArrayCellRenderer() - Constructor for class smile.swing.table.DoubleArrayCellRenderer

Constructor.

DoubleArrayList - Class in smile.util

A resizeable, array-backed list of double primitives.

DoubleArrayList() - Constructor for class smile.util.DoubleArrayList

Constructs an empty list.

DoubleArrayList(double[]) - Constructor for class smile.util.DoubleArrayList

Constructs a list containing the values of the specified array.

DoubleArrayList(int) - Constructor for class smile.util.DoubleArrayList

Constructs an empty list with the specified initial capacity.

DoubleArrayType - Static variable in class smile.data.type.DataTypes

Double Array data type.

DoubleCellEditor - Class in smile.swing.table

Implements a cell editor that uses a formatted text field to edit Double values.

DoubleCellEditor() - Constructor for class smile.swing.table.DoubleCellEditor

Constructor.

DoubleCellEditor(double, double) - Constructor for class smile.swing.table.DoubleCellEditor

Constructor.

DoubleConsumer - Interface in smile.math.matrix

Double precision matrix element stream consumer.

DoubleFunction - Class in smile.data.formula

The generic term of applying a double function.

DoubleFunction(String, Term, Function) - Constructor for class smile.data.formula.DoubleFunction

Constructor.

DoubleHeapSelect - Class in smile.sort

This class tracks the smallest values seen thus far in a stream of values.

DoubleHeapSelect(double[]) - Constructor for class smile.sort.DoubleHeapSelect

Constructor.

DoubleHeapSelect(int) - Constructor for class smile.sort.DoubleHeapSelect

Constructor.

DoubleObjectType - Static variable in class smile.data.type.DataTypes

Double Object data type.

DoubleType - Class in smile.data.type

Double data type.

DoubleType - Static variable in class smile.data.type.DataTypes

Double data type.

doubleValue() - Method in class smile.deep.tensor.Tensor

Returns the double value when the tensor holds a single value.

doubleVector(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

doubleVector(int) - Method in class smile.data.IndexDataFrame

doubleVector(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

doubleVector(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

DoubleVector - Interface in smile.data.vector

An immutable double vector.

download(String) - Static method in interface smile.util.CacheFiles

Downloads a file and save to the cache directory.

download(String, boolean) - Static method in interface smile.util.CacheFiles

Downloads a file and save to the cache directory.

drawLine(double[]...) - Method in class smile.plot.swing.Graphics

Draw poly line.

drawLineBaseRatio(double[]...) - Method in class smile.plot.swing.Graphics

Draw poly line.

drawPoint(char, double...) - Method in class smile.plot.swing.Graphics

Draw a dot with given pattern.

drawPoint(double...) - Method in class smile.plot.swing.Graphics

Draw a dot.

drawPolygon(double[]...) - Method in class smile.plot.swing.Graphics

Draw polygon.

drawRect(double[], double[]) - Method in class smile.plot.swing.Graphics

Draw the outline of the specified rectangle.

drawRectBaseRatio(double[], double[]) - Method in class smile.plot.swing.Graphics

Draw the outline of the specified rectangle.

drawText(String, double[]) - Method in class smile.plot.swing.Graphics

Draw a string.

drawText(String, double[], double) - Method in class smile.plot.swing.Graphics

Draw a string with given rotation angle.

drawText(String, double[], double, double) - Method in class smile.plot.swing.Graphics

Draw a string with given reference point.

drawText(String, double[], double, double, double) - Method in class smile.plot.swing.Graphics

Draw a string with given reference point and rotation angle.

drawTextBaseRatio(String, double[]) - Method in class smile.plot.swing.Graphics

Draw a string with given rotation angle.

drawTextBaseRatio(String, double[], double) - Method in class smile.plot.swing.Graphics

Draw a string with given rotation angle.

drawTextBaseRatio(String, double[], double, double) - Method in class smile.plot.swing.Graphics

Draw a string with given reference point.

drawTextBaseRatio(String, double[], double, double, double) - Method in class smile.plot.swing.Graphics

Draw a string with given reference point and rotation angle.

drop(int...) - Method in interface smile.data.DataFrame

Returns a new DataFrame without selected columns.

drop(int...) - Method in class smile.data.IndexDataFrame

drop(String...) - Method in interface smile.data.DataFrame

Returns a new DataFrame without selected columns.

dropout - Variable in class smile.base.mlp.Layer

The dropout rate.

dropout - Variable in class smile.base.mlp.LayerBuilder

The dropout rate.

dropout() - Method in record class smile.llm.Transformer.Options

Returns the value of the dropout record component.

dropout(double) - Static method in interface smile.deep.layer.Layer

Returns a dropout layer that randomly zeroes some of the elements of the input tensor with probability p during training.

dropout(double) - Method in class smile.deep.tensor.Tensor

Randomly zeroes some elements of the input tensor with probability p.

dropout_(double) - Method in class smile.deep.tensor.Tensor

Randomly zeroes some elements in place with probability p.

DropoutLayer - Class in smile.deep.layer

A dropout layer that randomly zeroes some of the elements of the input tensor with probability p during training.

DropoutLayer(double) - Constructor for class smile.deep.layer.DropoutLayer

Constructor.

DropoutLayer(double, boolean) - Constructor for class smile.deep.layer.DropoutLayer

Constructor.

dsv(String, String) - Method in class smile.plot.vega.Data

Loads a delimited text file with a custom delimiter.

dsv(String, String, Map<String, String>) - Method in class smile.plot.vega.Data

Loads a delimited text file with a custom delimiter.

DT - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Determiner.

dtype() - Method in class smile.deep.tensor.Tensor

Returns the element data type.

dtype(ScalarType) - Method in class smile.deep.tensor.Tensor.Options

Sets the data type of the elements stored in the tensor.

DUMMY - Enum constant in enum class smile.data.CategoricalEncoder

Dummy encoding.

DynamicTimeWarping<T> - Class in smile.math.distance

Dynamic time warping is an algorithm for measuring similarity between two sequences which may vary in time or speed.

DynamicTimeWarping(Distance<T>) - Constructor for class smile.math.distance.DynamicTimeWarping

Constructor.

DynamicTimeWarping(Distance<T>, double) - Constructor for class smile.math.distance.DynamicTimeWarping

Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.

E

Edge - Class in smile.vq.hebb

The connection between neurons.

Edge(int, int, double) - Constructor for class smile.graph.Graph.Edge

Constructor.

Edge(Neuron) - Constructor for class smile.vq.hebb.Edge

Constructor.

Edge(Neuron, int) - Constructor for class smile.vq.hebb.Edge

Constructor.

edges - Variable in class smile.vq.hebb.Neuron

The direct connected neighbors.

EditDistance - Class in smile.math.distance

The Edit distance between two strings is a metric for measuring the amount of difference between two sequences.

EditDistance() - Constructor for class smile.math.distance.EditDistance

Constructor.

EditDistance(boolean) - Constructor for class smile.math.distance.EditDistance

Constructor.

EditDistance(int) - Constructor for class smile.math.distance.EditDistance

Constructor.

EditDistance(int[][]) - Constructor for class smile.math.distance.EditDistance

Constructor.

EditDistance(int[][], double) - Constructor for class smile.math.distance.EditDistance

Constructor.

EditDistance(int, boolean) - Constructor for class smile.math.distance.EditDistance

Constructor.

EfficientNet - Class in smile.vision

EfficientNet is an image classification model family.

EfficientNet(MBConvConfig[], double, double, int, int, IntFunction<Layer>) - Constructor for class smile.vision.EfficientNet

Constructor.

eigen() - Method in class smile.math.matrix.BigMatrix

Eigenvalue Decomposition.

eigen() - Method in class smile.math.matrix.fp32.Matrix

Eigenvalue Decomposition.

eigen() - Method in class smile.math.matrix.Matrix

Eigenvalue Decomposition.

eigen(boolean, boolean, boolean) - Method in class smile.math.matrix.BigMatrix

Eigenvalue Decomposition.

eigen(boolean, boolean, boolean) - Method in class smile.math.matrix.fp32.Matrix

Eigenvalue Decomposition.

eigen(boolean, boolean, boolean) - Method in class smile.math.matrix.Matrix

Eigenvalue Decomposition.

eigen(double[]) - Method in class smile.math.matrix.IMatrix

Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.

eigen(double[], double, double, int) - Method in class smile.math.matrix.IMatrix

Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.

eigen(float[]) - Method in class smile.math.matrix.fp32.IMatrix

Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.

eigen(float[], float, float, int) - Method in class smile.math.matrix.fp32.IMatrix

Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.

eigen(IMatrix, ARPACK.AsymmOption, int) - Static method in class smile.math.matrix.fp32.ARPACK

Computes NEV eigenvalues of an asymmetric single precision matrix.

eigen(IMatrix, ARPACK.AsymmOption, int, int, float) - Static method in class smile.math.matrix.fp32.ARPACK

Computes NEV eigenvalues of an asymmetric single precision matrix.

eigen(IMatrix, int) - Static method in class smile.math.matrix.Lanczos

Find k largest approximate eigen pairs of a symmetric matrix by the Lanczos algorithm.

eigen(IMatrix, int, double, int) - Static method in class smile.math.matrix.Lanczos

Find k largest approximate eigen pairs of a symmetric matrix by the Lanczos algorithm.

eigen(IMatrix, ARPACK.AsymmOption, int) - Static method in class smile.math.matrix.ARPACK

Computes NEV eigenvalues of an asymmetric double precision matrix.

eigen(IMatrix, ARPACK.AsymmOption, int, int, double) - Static method in class smile.math.matrix.ARPACK

Computes NEV eigenvalues of an asymmetric double precision matrix.

EigenRange - Enum Class in smile.math.blas

THe option of eigenvalue range.

ElasticNet - Class in smile.regression

Elastic Net regularization.

ElasticNet() - Constructor for class smile.regression.ElasticNet

Ellipsis - Static variable in class smile.deep.tensor.Index

The ellipsis (...) is used to slice higher-dimensional data structures as in numpy.

EMAIL_ADDRESS - Static variable in interface smile.util.Regex

Email address.

embedding(int, int) - Static method in interface smile.deep.layer.Layer

Returns an embedding layer that is a simple lookup table that stores embeddings of a fixed dictionary and size.

embedding(int, int, double) - Static method in interface smile.deep.layer.Layer

Returns an embedding layer that is a simple lookup table that stores embeddings of a fixed dictionary and size.

EmbeddingLayer - Class in smile.deep.layer

An embedding layer that is a simple lookup table that stores embeddings of a fixed dictionary and size.

EmbeddingLayer(int, int) - Constructor for class smile.deep.layer.EmbeddingLayer

Constructor.

EmbeddingLayer(int, int, double) - Constructor for class smile.deep.layer.EmbeddingLayer

Constructor.

EmpiricalDistribution - Class in smile.stat.distribution

An empirical distribution function or empirical cdf, is a cumulative probability distribution function that concentrates probability 1/n at each of the n numbers in a sample.

EmpiricalDistribution(double[]) - Constructor for class smile.stat.distribution.EmpiricalDistribution

Constructor.

EmpiricalDistribution(double[], IntSet) - Constructor for class smile.stat.distribution.EmpiricalDistribution

Constructor.

empty(long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor with uninitialized data.

empty(Tensor.Options, long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor with uninitialized data.

emptyCache() - Method in class smile.deep.tensor.Device

Releases all unoccupied cached memory.

encode(String) - Method in class smile.llm.tokenizer.SentencePiece

encode(String) - Method in class smile.llm.tokenizer.Tiktoken

encode(String) - Method in interface smile.llm.tokenizer.Tokenizer

Encodes a string into a list of token IDs.

encode(String, boolean, boolean) - Method in class smile.llm.tokenizer.SentencePiece

encode(String, boolean, boolean) - Method in class smile.llm.tokenizer.Tiktoken

encode(String, boolean, boolean) - Method in interface smile.llm.tokenizer.Tokenizer

Encodes a string into a list of token IDs.

encode(String, String) - Method in class smile.plot.vega.View

Returns the field object for encoding a channel.

encodeDatum(String, double) - Method in class smile.plot.vega.Layer

encodeDatum(String, double) - Method in class smile.plot.vega.View

Sets a constant data value encoded via a scale.

encodeDatum(String, int) - Method in class smile.plot.vega.Layer

encodeDatum(String, int) - Method in class smile.plot.vega.View

Sets a constant data value encoded via a scale.

encodeDatum(String, String) - Method in class smile.plot.vega.Layer

encodeDatum(String, String) - Method in class smile.plot.vega.View

Sets a constant data value encoded via a scale.

encodeValue(String, double) - Method in class smile.plot.vega.Layer

encodeValue(String, double) - Method in class smile.plot.vega.View

Sets an encoded constant visual value.

encodeValue(String, int) - Method in class smile.plot.vega.Layer

encodeValue(String, int) - Method in class smile.plot.vega.View

Sets an encoded constant visual value.

encodeValue(String, String) - Method in class smile.plot.vega.Layer

encodeValue(String, String) - Method in class smile.plot.vega.View

Sets an encoded constant visual value.

engine - Static variable in interface smile.math.blas.BLAS

The default BLAS engine.

engine - Static variable in interface smile.math.blas.LAPACK

The default LAPACK engine.

EnglishDictionary - Enum Class in smile.nlp.dictionary

A concise dictionary of common terms in English.

EnglishPOSLexicon - Class in smile.nlp.pos

An English lexicon with part-of-speech tags.

EnglishPunctuations - Class in smile.nlp.dictionary

Punctuation marks in English.

EnglishStopWords - Enum Class in smile.nlp.dictionary

Several sets of English stop words.

ensemble(Classifier<T>...) - Static method in interface smile.classification.Classifier

Return an ensemble of multiple base models to obtain better predictive performance.

ensemble(DataFrameClassifier...) - Static method in interface smile.classification.DataFrameClassifier

Return an ensemble of multiple base models to obtain better predictive performance.

ensemble(DataFrameRegression...) - Static method in interface smile.regression.DataFrameRegression

Return an ensemble of multiple base models to obtain better predictive performance.

ensemble(Regression<T>...) - Static method in interface smile.regression.Regression

Return an ensemble of multiple base models to obtain better predictive performance.

ensureCapacity(int) - Method in class smile.util.DoubleArrayList

Increases the capacity, if necessary, to ensure that it can hold at least the number of values specified by the minimum capacity argument.

ensureCapacity(int) - Method in class smile.util.IntArrayList

Increases the capacity, if necessary, to ensure that it can hold at least the number of values specified by the minimum capacity argument.

entropy - Variable in class smile.clustering.MEC

The conditional entropy as the objective function.

entropy() - Method in class smile.stat.distribution.BernoulliDistribution

entropy() - Method in class smile.stat.distribution.BetaDistribution

entropy() - Method in class smile.stat.distribution.BinomialDistribution

entropy() - Method in class smile.stat.distribution.ChiSquareDistribution

entropy() - Method in class smile.stat.distribution.DiscreteMixture

Shannon entropy.

entropy() - Method in interface smile.stat.distribution.Distribution

Returns Shannon entropy of the distribution.

entropy() - Method in class smile.stat.distribution.EmpiricalDistribution

entropy() - Method in class smile.stat.distribution.ExponentialDistribution

entropy() - Method in class smile.stat.distribution.FDistribution

Shannon entropy.

entropy() - Method in class smile.stat.distribution.GammaDistribution

entropy() - Method in class smile.stat.distribution.GaussianDistribution

entropy() - Method in class smile.stat.distribution.GeometricDistribution

Shannon entropy.

entropy() - Method in class smile.stat.distribution.HyperGeometricDistribution

entropy() - Method in class smile.stat.distribution.KernelDensity

Shannon entropy.

entropy() - Method in class smile.stat.distribution.LogisticDistribution

entropy() - Method in class smile.stat.distribution.LogNormalDistribution

entropy() - Method in class smile.stat.distribution.Mixture

Shannon entropy.

entropy() - Method in interface smile.stat.distribution.MultivariateDistribution

Shannon entropy of the distribution.

entropy() - Method in class smile.stat.distribution.MultivariateGaussianDistribution

entropy() - Method in class smile.stat.distribution.MultivariateMixture

Shannon entropy.

entropy() - Method in class smile.stat.distribution.NegativeBinomialDistribution

Shannon entropy.

entropy() - Method in class smile.stat.distribution.PoissonDistribution

entropy() - Method in class smile.stat.distribution.ShiftedGeometricDistribution

entropy() - Method in class smile.stat.distribution.TDistribution

entropy() - Method in class smile.stat.distribution.WeibullDistribution

entropy(double[]) - Static method in class smile.math.MathEx

Shannon's entropy.

ENTROPY - Enum constant in enum class smile.base.cart.SplitRule

Used by the ID3, C4.5 and C5.0 tree generation algorithms.

entry - Variable in class smile.neighbor.lsh.Bucket

The indices of points that all have the same value for hash function g.

epsilon - Variable in class smile.base.mlp.MultilayerPerceptron

A small constant for numerical stability in RMSProp.

EPSILON - Static variable in interface smile.math.DifferentiableMultivariateFunction

A number close to zero, between machine epsilon and its square root.

EPSILON - Static variable in class smile.math.MathEx

The machine precision for the double type, which is the difference between 1 and the smallest value greater than 1 that is representable for the double type.

eq(double) - Method in class smile.deep.tensor.Tensor

Computes element-wise equality.

eq(int) - Method in class smile.deep.tensor.Tensor

Computes element-wise equality.

eq(Tensor) - Method in class smile.deep.tensor.Tensor

Computes element-wise equality.

equals(double[][], double[][]) - Static method in class smile.math.MathEx

Check if x element-wisely equals y with default epsilon 1E-10.

equals(double[][], double[][], double) - Static method in class smile.math.MathEx

Check if x element-wisely equals y in given precision.

equals(double[], double[]) - Static method in class smile.math.MathEx

Check if x element-wisely equals y with default epsilon 1E-10.

equals(double[], double[], double) - Static method in class smile.math.MathEx

Check if x element-wisely equals y in given precision.

equals(double, double) - Static method in class smile.math.MathEx

Returns true if two double values equals to each other in the system precision.

equals(float[][], float[][]) - Static method in class smile.math.MathEx

Check if x element-wisely equals y with default epsilon 1E-7.

equals(float[][], float[][], float) - Static method in class smile.math.MathEx

Check if x element-wisely equals y in given precision.

equals(float[], float[]) - Static method in class smile.math.MathEx

Check if x element-wisely equals y with default epsilon 1E-7.

equals(float[], float[], float) - Static method in class smile.math.MathEx

Check if x element-wisely equals y in given precision.

equals(Object) - Method in class smile.association.AssociationRule

equals(Object) - Method in class smile.association.ItemSet

equals(Object) - Method in class smile.base.cart.DecisionNode

equals(Object) - Method in class smile.base.cart.RegressionNode

equals(Object) - Method in class smile.data.formula.Formula

equals(Object) - Method in class smile.data.measure.CategoricalMeasure

equals(Object) - Method in class smile.data.measure.NominalScale

equals(Object) - Method in class smile.data.measure.OrdinalScale

equals(Object) - Method in record class smile.data.SampleInstance

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class smile.data.type.ArrayType

equals(Object) - Method in class smile.data.type.BooleanType

equals(Object) - Method in class smile.data.type.ByteType

equals(Object) - Method in class smile.data.type.CharType

equals(Object) - Method in class smile.data.type.DateTimeType

equals(Object) - Method in class smile.data.type.DateType

equals(Object) - Method in class smile.data.type.DecimalType

equals(Object) - Method in class smile.data.type.DoubleType

equals(Object) - Method in class smile.data.type.FloatType

equals(Object) - Method in class smile.data.type.IntegerType

equals(Object) - Method in class smile.data.type.LongType

equals(Object) - Method in class smile.data.type.ObjectType

equals(Object) - Method in class smile.data.type.ShortType

equals(Object) - Method in class smile.data.type.StringType

equals(Object) - Method in class smile.data.type.StructField

equals(Object) - Method in class smile.data.type.StructType

equals(Object) - Method in class smile.data.type.TimeType

equals(Object) - Method in record class smile.deep.SampleBatch

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class smile.deep.tensor.Device

equals(Object) - Method in class smile.deep.tensor.Tensor

equals(Object) - Method in record class smile.llm.Transformer.Options

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class smile.math.Complex

equals(Object) - Method in class smile.math.matrix.BandMatrix

equals(Object) - Method in class smile.math.matrix.BigMatrix

equals(Object) - Method in class smile.math.matrix.fp32.BandMatrix

equals(Object) - Method in class smile.math.matrix.fp32.Matrix

equals(Object) - Method in class smile.math.matrix.fp32.SymmMatrix

equals(Object) - Method in class smile.math.matrix.Matrix

equals(Object) - Method in class smile.math.matrix.SymmMatrix

equals(Object) - Method in class smile.nlp.Bigram

equals(Object) - Method in class smile.nlp.NGram

equals(Object) - Method in class smile.nlp.SimpleText

equals(Object) - Method in record class smile.plot.vega.SortField

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.plot.vega.WindowTransformField

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.util.Bytes

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.util.IntPair

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.util.Tuple2

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.vision.layer.MBConvConfig

Indicates whether some other object is "equal to" this one.

equals(BandMatrix, double) - Method in class smile.math.matrix.BandMatrix

Returns true if two matrices equal in given precision.

equals(BigMatrix, double) - Method in class smile.math.matrix.BigMatrix

Returns true if two matrices equal in given precision.

equals(BandMatrix, float) - Method in class smile.math.matrix.fp32.BandMatrix

Returns true if two matrices equal in given precision.

equals(Matrix, float) - Method in class smile.math.matrix.fp32.Matrix

Returns true if two matrices equal in given precision.

equals(SymmMatrix, float) - Method in class smile.math.matrix.fp32.SymmMatrix

Returns true if two matrices equal in given precision.

equals(Matrix, double) - Method in class smile.math.matrix.Matrix

Returns true if two matrices equal in given precision.

equals(SymmMatrix, double) - Method in class smile.math.matrix.SymmMatrix

Returns true if two matrices equal in given precision.

erf(double) - Static method in class smile.math.special.Erf

The Gauss error function.

Erf - Class in smile.math.special

The error function.

erfc(double) - Static method in class smile.math.special.Erf

The complementary error function.

erfcc(double) - Static method in class smile.math.special.Erf

The complementary error function with fractional error everywhere less than 1.2 × 10^-7.

error - Variable in class smile.validation.ClassificationMetrics

The number of errors.

error() - Method in class smile.regression.LinearModel

Returns the residual standard error.

Error - Class in smile.validation.metric

The number of errors in the population.

Error() - Constructor for class smile.validation.metric.Error

ERROR_OPTION - Static variable in class smile.swing.FontChooser

Return value from showDialog().

estimate(int, double) - Method in class smile.neighbor.lsh.HashValueParzenModel

Given a hash value h, estimate the Gaussian model (mean and variance) of neighbors existing in the corresponding bucket.

EuclideanDistance - Class in smile.math.distance

Euclidean distance.

EuclideanDistance() - Constructor for class smile.math.distance.EuclideanDistance

Constructor.

EuclideanDistance(double[]) - Constructor for class smile.math.distance.EuclideanDistance

Constructor with a given weight vector.

eval() - Method in class smile.deep.Model

Sets the model in the evaluation/inference mode.

eval(Dataset, Metric...) - Method in class smile.deep.Model

Evaluates the model accuracy on a test dataset.

EVD(double[], double[], Matrix, Matrix) - Constructor for class smile.math.matrix.Matrix.EVD

Constructor.

EVD(double[], Matrix) - Constructor for class smile.math.matrix.Matrix.EVD

Constructor.

EVD(float[], float[], Matrix, Matrix) - Constructor for class smile.math.matrix.fp32.Matrix.EVD

Constructor.

EVD(float[], Matrix) - Constructor for class smile.math.matrix.fp32.Matrix.EVD

Constructor.

EVD(DoublePointer, DoublePointer, BigMatrix, BigMatrix) - Constructor for class smile.math.matrix.BigMatrix.EVD

Constructor.

EVD(DoublePointer, BigMatrix) - Constructor for class smile.math.matrix.BigMatrix.EVD

Constructor.

EVDJob - Enum Class in smile.math.blas

The option if computing eigen vectors.

evolve() - Method in interface smile.gap.LamarckianChromosome

Performs a step of (hill-climbing) local search to evolve this chromosome.

evolve(int) - Method in class smile.gap.GeneticAlgorithm

Performs genetic algorithm for a given number of generations.

evolve(int, double) - Method in class smile.gap.GeneticAlgorithm

Performs genetic algorithm until the given number of generations is reached or the best fitness is larger than the given threshold.

EX - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Existential there.

execute(String) - Method in class smile.data.SQL

Executes an SQL statement, which may return multiple results.

exp() - Method in class smile.deep.tensor.Tensor

Returns the exponential of elements in the tensor.

exp() - Method in class smile.math.Complex

Returns the complex exponential.

exp(double, double) - Static method in interface smile.math.TimeFunction

Returns the exponential decay function.

exp(double, double, double) - Static method in interface smile.math.TimeFunction

Returns the exponential decay function.

exp(double, double, double, boolean) - Static method in interface smile.math.TimeFunction

Returns the exponential decay function.

exp(String) - Static method in interface smile.data.formula.Terms

The exp(x) term.

exp(Term) - Static method in interface smile.data.formula.Terms

The exp(x) term.

Exp - Class in smile.ica

The contrast function when the independent components are highly super-Gaussian, or when robustness is very important.

Exp() - Constructor for class smile.ica.Exp

exp_() - Method in class smile.deep.tensor.Tensor

Returns the exponential of elements in the tensor in place.

expand() - Method in class smile.data.formula.FactorCrossing

expand() - Method in interface smile.data.formula.Term

Expands the term (e.g.

expand() - Method in class smile.neighbor.lsh.Probe

This operation sets to one the component following the last nonzero component if it is not the last one.

expand(StructType) - Method in class smile.data.formula.Formula

Expands the Dot and FactorCrossing terms on the given schema.

expandRatio() - Method in record class smile.vision.layer.MBConvConfig

Returns the value of the expandRatio record component.

expm1(String) - Static method in interface smile.data.formula.Terms

The exp(x) - 1 term.

expm1(Term) - Static method in interface smile.data.formula.Terms

The exp(x) - 1 term.

ExponentialDistribution - Class in smile.stat.distribution

An exponential distribution describes the times between events in a Poisson process, in which events occur continuously and independently at a constant average rate.

ExponentialDistribution(double) - Constructor for class smile.stat.distribution.ExponentialDistribution

Constructor.

ExponentialFamily - Interface in smile.stat.distribution

The exponential family is a class of probability distributions sharing a certain form.

ExponentialFamilyMixture - Class in smile.stat.distribution

The finite mixture of distributions from exponential family.

ExponentialFamilyMixture(Mixture.Component...) - Constructor for class smile.stat.distribution.ExponentialFamilyMixture

Constructor.

ExponentialVariogram - Class in smile.interpolation.variogram

Exponential variogram.

ExponentialVariogram(double, double) - Constructor for class smile.interpolation.variogram.ExponentialVariogram

Constructor.

ExponentialVariogram(double, double, double) - Constructor for class smile.interpolation.variogram.ExponentialVariogram

Constructor.

extend() - Method in class smile.neighbor.lsh.Probe

This operation adds one to the last nonzero component.

extendBound(double[], double[]) - Method in class smile.plot.swing.Base

Extend lower and upper bounds.

extendBound(double[], double[]) - Method in class smile.plot.swing.Canvas

Extend lower and upper bounds.

extendBound(int) - Method in class smile.plot.swing.Base

Rounds the bounds for axis i.

extendLowerBound(double[]) - Method in class smile.plot.swing.Base

Extend lower bounds.

extendLowerBound(double[]) - Method in class smile.plot.swing.Canvas

Extend lower bounds.

extendUpperBound(double[]) - Method in class smile.plot.swing.Base

Extend upper bounds.

extendUpperBound(double[]) - Method in class smile.plot.swing.Canvas

Extend upper bounds.

extent(double, double) - Method in class smile.plot.vega.BinParams

Sets the range of desired bin values

extent(double, double) - Method in class smile.plot.vega.DensityTransform

Sets a [min, max] domain from which to sample the distribution.

extent(double, double) - Method in class smile.plot.vega.RegressionTransform

Sets a [min, max] domain over the independent (x) field for the starting and ending points of the generated trend line.

extent(String) - Method in class smile.plot.vega.Mark

Sets the extent of the band.

extent(String, String) - Method in class smile.plot.vega.Transform

Adds an extent transform.

eye(int) - Static method in class smile.math.matrix.BigMatrix

Returns an identity matrix.

eye(int) - Static method in class smile.math.matrix.fp32.Matrix

Returns an identity matrix.

eye(int) - Static method in class smile.math.matrix.Matrix

Returns an identity matrix.

eye(int, int) - Static method in class smile.math.matrix.BigMatrix

Returns an m-by-n identity matrix.

eye(int, int) - Static method in class smile.math.matrix.fp32.Matrix

Returns an m-by-n identity matrix.

eye(int, int) - Static method in class smile.math.matrix.Matrix

Returns an m-by-n identity matrix.

eye(long) - Static method in class smile.deep.tensor.Tensor

Returns an identity matrix.

eye(Tensor.Options, long) - Static method in class smile.deep.tensor.Tensor

Returns an identity matrix.

F

f - Variable in class smile.stat.hypothesis.FTest

F-statistic.

f(double) - Method in class smile.ica.Exp

f(double) - Method in class smile.ica.Kurtosis

f(double) - Method in class smile.ica.LogCosh

f(double) - Method in class smile.interpolation.variogram.ExponentialVariogram

f(double) - Method in class smile.interpolation.variogram.GaussianVariogram

f(double) - Method in class smile.interpolation.variogram.PowerVariogram

f(double) - Method in class smile.interpolation.variogram.SphericalVariogram

f(double) - Method in interface smile.math.Function

Computes the value of the function at x.

f(double) - Method in interface smile.math.kernel.DotProductKernel

f(double) - Method in interface smile.math.kernel.IsotropicKernel

f(double) - Method in class smile.math.kernel.Matern

f(double) - Method in class smile.math.rbf.GaussianRadialBasis

f(double) - Method in class smile.math.rbf.InverseMultiquadricRadialBasis

f(double) - Method in class smile.math.rbf.MultiquadricRadialBasis

f(double) - Method in class smile.math.rbf.ThinPlateRadialBasis

f(double) - Method in class smile.math.Scaler

f(double[]) - Method in interface smile.base.mlp.activation.ActivationFunction

The output function.

f(double[]) - Method in class smile.base.mlp.activation.LeakyReLU

f(double[]) - Method in class smile.base.mlp.activation.ReLU

f(double[]) - Method in class smile.base.mlp.activation.Sigmoid

f(double[]) - Method in class smile.base.mlp.activation.Softmax

f(double[]) - Method in class smile.base.mlp.activation.Tanh

f(double[]) - Method in interface smile.base.mlp.ActivationFunction

The output function.

f(double[]) - Method in enum class smile.base.mlp.OutputFunction

The output function.

f(double[]) - Method in class smile.base.svm.LinearKernelMachine

Returns the value of decision function.

f(double[]) - Method in interface smile.math.MultivariateFunction

Computes the value of the function at x.

f(int) - Method in interface smile.math.IntFunction

Computes the value of the function at x.

f(int[]) - Method in class smile.base.svm.LinearKernelMachine

Returns the value of decision function.

f(SparseArray) - Method in class smile.base.svm.LinearKernelMachine

Returns the value of decision function.

f(T) - Method in class smile.base.rbf.RBF

The activation function.

f1 - Variable in class smile.validation.ClassificationMetrics

The F-1 score on validation data.

F1 - Static variable in class smile.validation.metric.FScore

The F_1 score, the harmonic mean of precision and recall.

F2 - Static variable in class smile.validation.metric.FScore

The F_2 score, which weighs recall higher than precision.

facet(String) - Method in class smile.plot.vega.Facet

Returns the field definition for faceting the plot by one field.

Facet - Class in smile.plot.vega

A facet is a trellis plot (or small multiple) of a series of similar plots that displays different subsets of the same data, facilitating comparison across subsets.

Facet(VegaLite) - Constructor for class smile.plot.vega.Facet

Constructor.

FacetField - Class in smile.plot.vega

Facet field definition object.

factor(int) - Method in class smile.data.measure.CategoricalMeasure

Returns the factor value (in range [0, size)) of level.

FactorCrossing - Class in smile.data.formula

Factor crossing.

FactorCrossing(int, String...) - Constructor for class smile.data.formula.FactorCrossing

Constructor.

FactorCrossing(String...) - Constructor for class smile.data.formula.FactorCrossing

Constructor.

factorial(int) - Static method in class smile.math.MathEx

The factorial of n.

FactorInteraction - Class in smile.data.formula

The interaction of all the factors appearing in the term.

FactorInteraction(String...) - Constructor for class smile.data.formula.FactorInteraction

Constructor.

factorize(String...) - Method in interface smile.data.DataFrame

Returns a new DataFrame with given columns converted to nominal.

factorize(CategoricalMeasure) - Method in interface smile.data.vector.StringVector

Converts strings to discrete measured values.

Fallout - Class in smile.validation.metric

Fall-out, false alarm rate, or false positive rate (FPR)

Fallout() - Constructor for class smile.validation.metric.Fallout

falseChild() - Method in class smile.base.cart.InternalNode

Returns the false branch child.

FDistribution - Class in smile.stat.distribution

F-distribution arises in the testing of whether two observed samples have the same variance.

FDistribution(int, int) - Constructor for class smile.stat.distribution.FDistribution

Constructor.

FDR - Class in smile.validation.metric

The false discovery rate (FDR) is ratio of false positives to combined true and false positives, which is actually 1 - precision.

FDR() - Constructor for class smile.validation.metric.FDR

feature - Variable in class smile.feature.selection.InformationValue

The feature name.

feature - Variable in class smile.feature.selection.SignalNoiseRatio

The feature name.

feature - Variable in class smile.feature.selection.SumSquaresRatio

The feature name.

feature() - Method in class smile.base.cart.InternalNode

Returns the split feature.

Feature - Interface in smile.data.formula

A feature in the formula once bound to a schema.

features - Variable in class smile.sequence.CRFLabeler

The feature function.

features() - Method in class smile.feature.extraction.BagOfWords

Returns the feature words.

features() - Method in class smile.vision.EfficientNet

Returns the feature layer block.

FHalf - Static variable in class smile.validation.metric.FScore

The F_0.5 score, which weighs recall lower than precision.

field() - Method in interface smile.data.formula.Feature

Returns the meta data of feature.

field() - Method in interface smile.data.vector.BaseVector

Returns a struct field corresponding to this vector.

field() - Method in record class smile.plot.vega.SortField

Returns the value of the field record component.

field() - Method in record class smile.plot.vega.WindowTransformField

Returns the value of the field record component.

field(int) - Method in class smile.data.type.StructType

Return the field at position i.

field(String) - Method in class smile.data.type.StructType

Return the field of given name.

Field - Class in smile.plot.vega

Encoding field definition object.

fields() - Method in class smile.data.type.StructType

Returns the fields.

fields(String...) - Method in class smile.plot.vega.LookupData

Returns the fields in foreign data or selection to lookup..

fieldTitle(String) - Method in class smile.plot.vega.Config

Defines how Vega-Lite generates title for fields.

file(String) - Static method in interface smile.io.HadoopInput

Returns the Parquet's InputFile instance of a file path or URI.

FileChooser - Class in smile.swing

File chooser for with file/images preview.

FileChooser() - Constructor for class smile.swing.FileChooser

Constructor.

FileChooser.SimpleFileFilter - Class in smile.swing

A simple extension-based file filter.

fill(char, int) - Static method in interface smile.util.Strings

Returns the string with a single repeated character to a specific length.

fill(double) - Method in class smile.math.matrix.BigMatrix

Fill the matrix with a value.

fill(double) - Method in class smile.math.matrix.Matrix

Fills the matrix with a value.

fill(float) - Method in class smile.math.matrix.fp32.Matrix

Fills the matrix with a value.

fill(String) - Method in class smile.plot.vega.Background

Sets the fill color.

fill(String) - Method in class smile.plot.vega.Mark

Sets the default fill color.

fill(String) - Method in class smile.plot.vega.ViewConfig

Sets the fill color.

fill_(double) - Method in class smile.deep.tensor.Tensor

Fills this tensor with the specified value.

fill_(int) - Method in class smile.deep.tensor.Tensor

Fills this tensor with the specified value.

fillColor(String) - Method in class smile.plot.vega.Legend

Sets the background fill color for the full legend.

filled(boolean) - Method in class smile.plot.vega.Mark

Sets whether the mark's color should be used as fill color instead of stroke color.

fillOpacity(double) - Method in class smile.plot.vega.Background

Sets the fill opacity.

fillOpacity(double) - Method in class smile.plot.vega.Mark

Sets the fill opacity.

fillOpacity(double) - Method in class smile.plot.vega.ViewConfig

Sets the fill opacity.

fillPolygon(double[]...) - Method in class smile.plot.swing.Graphics

Fill polygon.

fillPolygon(float, double[]...) - Method in class smile.plot.swing.Graphics

Fill polygon.

fillRect(double[], double[]) - Method in class smile.plot.swing.Graphics

Fill the specified rectangle.

fillRectBaseRatio(double[], double[]) - Method in class smile.plot.swing.Graphics

Fill the specified rectangle.

filter(String) - Method in class smile.plot.vega.Transform

Adds a filter transform.

filter(Predicate) - Method in class smile.plot.vega.Transform

Adds a filter transform.

find(DifferentiableFunction, double, double, double, int) - Static method in class smile.math.Root

Newton's method (also known as the Newton–Raphson method).

find(Function, double, double, double, int) - Static method in class smile.math.Root

Brent's method for root-finding.

findBestSplit(LeafNode, int, double, int, int) - Method in class smile.base.cart.CART

Finds the best split for given column.

findBestSplit(LeafNode, int, double, int, int) - Method in class smile.classification.DecisionTree

findBestSplit(LeafNode, int, double, int, int) - Method in class smile.regression.RegressionTree

findBestSplit(LeafNode, int, int, boolean[]) - Method in class smile.base.cart.CART

Finds the best attribute to split on a set of samples.

fit(double[]) - Static method in class smile.stat.distribution.BetaDistribution

Estimates the distribution parameters by the moment method.

fit(double[]) - Static method in class smile.stat.distribution.ExponentialDistribution

Estimates the distribution parameters by MLE.

fit(double[]) - Static method in class smile.stat.distribution.GammaDistribution

Estimates the distribution parameters by (approximate) MLE.

fit(double[]) - Static method in class smile.stat.distribution.GaussianDistribution

Estimates the distribution parameters by MLE.

fit(double[]) - Static method in class smile.stat.distribution.GaussianMixture

Fits the Gaussian mixture model with the EM algorithm.

fit(double[]) - Static method in class smile.stat.distribution.LogNormalDistribution

Estimates the distribution parameters by MLE.

fit(double[][]) - Static method in class smile.anomaly.IsolationForest

Fits an isolation forest.

fit(double[][]) - Static method in class smile.stat.distribution.MultivariateGaussianDistribution

Estimates the mean and diagonal covariance by MLE.

fit(double[][]) - Static method in class smile.stat.distribution.MultivariateGaussianMixture

Fits the Gaussian mixture model with the EM algorithm.

fit(double[][], boolean) - Static method in class smile.stat.distribution.MultivariateGaussianDistribution

Estimates the mean and covariance by MLE.

fit(double[][], boolean) - Static method in class smile.stat.distribution.MultivariateGaussianMixture

Fits the Gaussian mixture model with the EM algorithm.

fit(double[][], double[], double, double, double) - Static method in class smile.regression.SVM

Fits a linear epsilon-SVR.

fit(double[][], double[], Properties) - Static method in class smile.regression.GaussianProcessRegression

Fits a regular Gaussian process model.

fit(double[][], double[], Properties) - Static method in class smile.regression.MLP

Fits a MLP model.

fit(double[][], double[], Properties) - Static method in class smile.regression.RBFNetwork

Fits a RBF network.

fit(double[][], double[], Properties) - Static method in class smile.regression.SVM

Fits an epsilon-SVR.

fit(double[][], double, int) - Static method in class smile.clustering.DENCLUE

Clustering data.

fit(double[][], double, int, double, int) - Static method in class smile.clustering.DENCLUE

Clustering data.

fit(double[][], int) - Static method in class smile.base.rbf.RBF

Fits Gaussian RBF function and centers on data.

fit(double[][], int) - Static method in class smile.clustering.DeterministicAnnealing

Clustering data into k clusters.

fit(double[][], int) - Static method in class smile.clustering.GMeans

Clustering data with the number of clusters determined by G-Means algorithm automatically.

fit(double[][], int) - Static method in class smile.clustering.KMeans

Partitions data into k clusters up to 100 iterations.

fit(double[][], int) - Static method in class smile.clustering.XMeans

Clustering data with the number of clusters determined by X-Means algorithm automatically.

fit(double[][], int) - Static method in class smile.ica.ICA

Fits independent component analysis.

fit(double[][], int[]) - Static method in class smile.classification.FLD

Fits Fisher's linear discriminant.

fit(double[][], int[]) - Static method in class smile.classification.KNN

Fits the 1-NN classifier.

fit(double[][], int[]) - Static method in class smile.classification.LDA

Fits linear discriminant analysis.

fit(double[][], int[]) - Static method in class smile.classification.LogisticRegression

Fits logistic regression.

fit(double[][], int[]) - Static method in class smile.classification.QDA

Fits quadratic discriminant analysis.

fit(double[][], int[], double) - Static method in class smile.classification.RDA

Fits regularized discriminant analysis.

fit(double[][], int[], double[], double) - Static method in class smile.classification.LDA

Fits linear discriminant analysis.

fit(double[][], int[], double[], double) - Static method in class smile.classification.QDA

Fits quadratic discriminant analysis.

fit(double[][], int[], double, double) - Static method in class smile.classification.SVM

Fits a binary linear SVM.

fit(double[][], int[], double, double[], double) - Static method in class smile.classification.RDA

Fits regularized discriminant analysis.

fit(double[][], int[], double, double, int) - Static method in class smile.classification.LogisticRegression

Fits logistic regression.

fit(double[][], int[], double, double, int) - Static method in class smile.classification.SVM

Fits a binary linear SVM.

fit(double[][], int[], int) - Static method in class smile.classification.KNN

Fits the K-NN classifier.

fit(double[][], int[], int, double) - Static method in class smile.classification.FLD

Fits Fisher's linear discriminant.

fit(double[][], int[], Properties) - Static method in class smile.classification.FLD

Fits Fisher's linear discriminant.

fit(double[][], int[], Properties) - Static method in class smile.classification.LDA

Fits linear discriminant analysis.

fit(double[][], int[], Properties) - Static method in class smile.classification.LogisticRegression

Fits logistic regression.

fit(double[][], int[], Properties) - Static method in class smile.classification.MLP

Fits a MLP model.

fit(double[][], int[], Properties) - Static method in class smile.classification.QDA

Fits quadratic discriminant analysis.

fit(double[][], int[], Properties) - Static method in class smile.classification.RBFNetwork

Fits a RBF network.

fit(double[][], int[], Properties) - Static method in class smile.classification.RDA

Fits regularized discriminant analysis.

fit(double[][], int[], Properties) - Static method in class smile.classification.SVM

Fits a binary or multiclass SVM.

fit(double[][], int, double) - Static method in class smile.base.rbf.RBF

Fits Gaussian RBF function and centers on data.

fit(double[][], int, double) - Static method in class smile.clustering.DBSCAN

Clustering the data with KD-tree.

fit(double[][], int, double) - Static method in class smile.clustering.SpectralClustering

Spectral clustering the data.

fit(double[][], int, double, int, double) - Static method in class smile.clustering.SpectralClustering

Spectral clustering the data.

fit(double[][], int, double, int, double, double) - Static method in class smile.clustering.DeterministicAnnealing

Clustering data into k clusters.

fit(double[][], int, int) - Static method in class smile.base.rbf.RBF

Fits Gaussian RBF function and centers on data.

fit(double[][], int, int, double) - Static method in class smile.clustering.GMeans

Clustering data with the number of clusters determined by G-Means algorithm automatically.

fit(double[][], int, int, double) - Static method in class smile.clustering.KMeans

Partitions data into k clusters up to 100 iterations.

fit(double[][], int, int, double) - Static method in class smile.clustering.SpectralClustering

Spectral clustering with Nystrom approximation.

fit(double[][], int, int, double) - Static method in class smile.clustering.XMeans

Clustering data with the number of clusters determined by X-Means algorithm automatically.

fit(double[][], int, int, double, int) - Static method in class smile.anomaly.IsolationForest

Fits a random forest for classification.

fit(double[][], int, int, double, int, double) - Static method in class smile.clustering.SpectralClustering

Spectral clustering with Nystrom approximation.

fit(double[][], int, String...) - Static method in class smile.feature.extraction.ProbabilisticPCA

Fits probabilistic principal component analysis.

fit(double[][], int, Properties) - Static method in class smile.ica.ICA

Fits independent component analysis.

fit(double[][], int, DifferentiableFunction, double, int) - Static method in class smile.ica.ICA

Fits independent component analysis.

fit(double[][], String...) - Static method in class smile.feature.extraction.PCA

Fits principal component analysis with covariance matrix.

fit(double[][], Properties) - Static method in class smile.anomaly.IsolationForest

Fits a random forest for classification.

fit(double[][], MultivariateMixture.Component...) - Static method in class smile.stat.distribution.MultivariateExponentialFamilyMixture

Fits the mixture model with the EM algorithm.

fit(double[][], MultivariateMixture.Component[], double, int, double) - Static method in class smile.stat.distribution.MultivariateExponentialFamilyMixture

Fits the mixture model with the EM algorithm.

fit(double[], int) - Static method in class smile.timeseries.AR

Fits an autoregressive model with Yule-Walker procedure.

fit(double[], int[]) - Static method in class smile.classification.IsotonicRegressionScaling

Trains the Isotonic Regression scaling.

fit(double[], int[]) - Static method in class smile.classification.PlattScaling

Trains the Platt scaling.

fit(double[], int[], int) - Static method in class smile.classification.PlattScaling

Trains the Platt scaling.

fit(double[], int, int) - Static method in class smile.timeseries.ARMA

Fits an ARMA model with Hannan-Rissanen algorithm.

fit(double[], Mixture.Component...) - Static method in class smile.stat.distribution.ExponentialFamilyMixture

Fits the mixture model with the EM algorithm.

fit(double[], Mixture.Component[], double, int, double) - Static method in class smile.stat.distribution.ExponentialFamilyMixture

Fits the mixture model with the EM algorithm.

fit(int[]) - Static method in class smile.classification.ClassLabels

Fits the class label mapping.

fit(int[]) - Static method in class smile.stat.distribution.BernoulliDistribution

Estimates the distribution parameters by MLE.

fit(int[]) - Static method in class smile.stat.distribution.EmpiricalDistribution

Estimates the distribution.

fit(int[]) - Static method in class smile.stat.distribution.GeometricDistribution

Estimates the distribution parameters by MLE.

fit(int[]) - Static method in class smile.stat.distribution.PoissonDistribution

Estimates the distribution parameters by MLE.

fit(int[]) - Static method in class smile.stat.distribution.ShiftedGeometricDistribution

Estimates the distribution parameters by MLE.

fit(int[][], double[], int, double, double, double) - Static method in class smile.regression.SVM

Fits a linear epsilon-SVR of binary sparse data.

fit(int[][], int) - Static method in class smile.clustering.KModes

Fits k-modes clustering.

fit(int[][], int[][]) - Static method in class smile.sequence.HMM

Fits an HMM by maximum likelihood estimation.

fit(int[][], int[], int, double, double) - Static method in class smile.classification.SVM

Fits a binary linear SVM of binary sparse data.

fit(int[][], int[], int, double, double, int) - Static method in class smile.classification.SVM

Fits a binary linear SVM of binary sparse data.

fit(int[][], int, int) - Static method in class smile.clustering.KModes

Fits k-modes clustering.

fit(int[], DiscreteMixture.Component...) - Static method in class smile.stat.distribution.DiscreteExponentialFamilyMixture

Fits the mixture model with the EM algorithm.

fit(int[], DiscreteMixture.Component[], double, int, double) - Static method in class smile.stat.distribution.DiscreteExponentialFamilyMixture

Fits the mixture model with the EM algorithm.

fit(int[], IntSet) - Static method in class smile.stat.distribution.EmpiricalDistribution

Estimates the distribution.

fit(int, double[]) - Static method in class smile.stat.distribution.GaussianMixture

Fits the Gaussian mixture model with the EM algorithm.

fit(int, double[][]) - Static method in class smile.stat.distribution.MultivariateGaussianMixture

Fits the Gaussian mixture model with the EM algorithm.

fit(int, double[][], boolean) - Static method in class smile.stat.distribution.MultivariateGaussianMixture

Fits the Gaussian mixture model with the EM algorithm.

fit(int, int[][], int[]) - Static method in class smile.classification.Maxent

Fits maximum entropy classifier.

fit(int, int[][], int[], double, double, int) - Static method in class smile.classification.Maxent

Fits maximum entropy classifier.

fit(int, int[][], int[], Properties) - Static method in class smile.classification.Maxent

Fits maximum entropy classifier.

fit(String[][], PennTreebankPOS[][]) - Static method in class smile.nlp.pos.HMMPOSTagger

Fits an HMM POS tagger by maximum likelihood estimation.

fit(Classifier<T>, T[], int[]) - Static method in class smile.classification.PlattScaling

Fits Platt Scaling to estimate posteriori probabilities.

fit(BBDTree, double[][], int, int, double) - Static method in class smile.clustering.KMeans

Partitions data into k clusters.

fit(Linkage) - Static method in class smile.clustering.HierarchicalClustering

Fits the Agglomerative Hierarchical Clustering with given linkage method, which includes proximity matrix.

fit(DataFrame) - Static method in class smile.feature.transform.WinsorScaler

Fits the data transformation with 5% lower limit and 95% upper limit.

fit(DataFrame, double, double, String...) - Static method in class smile.feature.imputation.SimpleImputer

Fits the missing value imputation values.

fit(DataFrame, double, double, String...) - Static method in class smile.feature.transform.WinsorScaler

Fits the data transformation.

fit(DataFrame, int, String...) - Static method in class smile.feature.extraction.ProbabilisticPCA

Fits probabilistic principal component analysis.

fit(DataFrame, String) - Static method in class smile.feature.selection.InformationValue

Calculates the information value.

fit(DataFrame, String) - Static method in class smile.feature.selection.SignalNoiseRatio

Calculates the signal noise ratio of numeric variables.

fit(DataFrame, String) - Static method in class smile.feature.selection.SumSquaresRatio

Calculates the sum squares ratio of numeric variables.

fit(DataFrame, String...) - Static method in class smile.feature.extraction.PCA

Fits principal component analysis with covariance matrix.

fit(DataFrame, String...) - Static method in class smile.feature.imputation.SimpleImputer

Fits the missing value imputation values.

fit(DataFrame, String...) - Static method in class smile.feature.transform.MaxAbsScaler

Fits the data transformation.

fit(DataFrame, String...) - Static method in class smile.feature.transform.RobustStandardizer

Fits the data transformation.

fit(DataFrame, String...) - Static method in class smile.feature.transform.Scaler

Fits the data transformation.

fit(DataFrame, String...) - Static method in class smile.feature.transform.Standardizer

Fits the data transformation.

fit(DataFrame, String, int) - Static method in class smile.feature.selection.InformationValue

Calculates the information value.

fit(DataFrame, Function<String, String[]>, int, String...) - Static method in class smile.feature.extraction.BagOfWords

Learns a vocabulary dictionary of top-k frequent tokens in the raw documents.

fit(DataFrame, Function<DataFrame, Transform>...) - Static method in interface smile.data.transform.Transform

Fits a pipeline of data transforms.

fit(DataFrame, Distance<Tuple>, int) - Static method in class smile.feature.imputation.KMedoidsImputer

Fits the missing value imputation values.

fit(DataFrame, MercerKernel<double[]>, int, double, String...) - Static method in class smile.feature.extraction.KernelPCA

Fits kernel principal component analysis.

fit(DataFrame, MercerKernel<double[]>, int, String...) - Static method in class smile.feature.extraction.KernelPCA

Fits kernel principal component analysis.

fit(Dataset<?, Integer>) - Static method in class smile.classification.ClassLabels

Fits the class label mapping.

fit(Formula, DataFrame) - Static method in class smile.classification.AdaBoost

Fits a AdaBoost model.

fit(Formula, DataFrame) - Method in interface smile.classification.DataFrameClassifier.Trainer

Fits a classification model with the default hyper-parameters.

fit(Formula, DataFrame) - Static method in class smile.classification.DecisionTree

Fits a classification tree.

fit(Formula, DataFrame) - Static method in class smile.classification.GradientTreeBoost

Fits a gradient tree boosting for classification.

fit(Formula, DataFrame) - Static method in class smile.classification.RandomForest

Fits a random forest for classification.

fit(Formula, DataFrame) - Method in interface smile.regression.DataFrameRegression.Trainer

Fits a regression model with the default hyper-parameters.

fit(Formula, DataFrame) - Static method in class smile.regression.GradientTreeBoost

Fits a gradient tree boosting for regression.

fit(Formula, DataFrame) - Static method in class smile.regression.LASSO

Fits a L1-regularized least squares model.

fit(Formula, DataFrame) - Static method in class smile.regression.OLS

Fits an ordinary least squares model.

fit(Formula, DataFrame) - Static method in class smile.regression.RandomForest

Fits a random forest for regression.

fit(Formula, DataFrame) - Static method in class smile.regression.RegressionTree

Fits a regression tree.

fit(Formula, DataFrame) - Static method in class smile.regression.RidgeRegression

Fits a ridge regression model.

fit(Formula, DataFrame, double) - Static method in class smile.regression.LASSO

Fits a L1-regularized least squares model.

fit(Formula, DataFrame, double) - Static method in class smile.regression.RidgeRegression

Fits a ridge regression model.

fit(Formula, DataFrame, double[], double[], double[]) - Static method in class smile.regression.RidgeRegression

Fits a generalized ridge regression model that minimizes a weighted least squares criterion augmented with a generalized ridge penalty:

fit(Formula, DataFrame, double, double) - Static method in class smile.regression.ElasticNet

Fits an Elastic Net model.

fit(Formula, DataFrame, double, double, double, int) - Static method in class smile.regression.ElasticNet

Fits an Elastic Net model.

fit(Formula, DataFrame, double, double, int) - Static method in class smile.regression.LASSO

Fits a L1-regularized least squares model.

fit(Formula, DataFrame, int, int, int) - Static method in class smile.regression.RegressionTree

Fits a regression tree.

fit(Formula, DataFrame, int, int, int, int) - Static method in class smile.classification.AdaBoost

Fits a AdaBoost model.

fit(Formula, DataFrame, int, int, int, int, double, double) - Static method in class smile.classification.GradientTreeBoost

Fits a gradient tree boosting for classification.

fit(Formula, DataFrame, int, int, int, int, int, double) - Static method in class smile.regression.RandomForest

Fits a random forest for regression.

fit(Formula, DataFrame, int, int, int, int, int, double, LongStream) - Static method in class smile.regression.RandomForest

Fits a random forest for regression.

fit(Formula, DataFrame, int, int, SplitRule, int, int, int, double) - Static method in class smile.classification.RandomForest

Fits a random forest for classification.

fit(Formula, DataFrame, int, int, SplitRule, int, int, int, double, int[]) - Static method in class smile.classification.RandomForest

Fits a random forest for regression.

fit(Formula, DataFrame, int, int, SplitRule, int, int, int, double, int[], LongStream) - Static method in class smile.classification.RandomForest

Fits a random forest for classification.

fit(Formula, DataFrame, String, boolean, boolean) - Static method in class smile.regression.OLS

Fits an ordinary least squares model.

fit(Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in class smile.classification.OneVersusOne

Fits a multi-class model with binary data frame classifiers.

fit(Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in class smile.classification.OneVersusRest

Fits a multi-class model with binary data frame classifiers.

fit(Formula, DataFrame, Properties) - Static method in class smile.classification.AdaBoost

Fits a AdaBoost model.

fit(Formula, DataFrame, Properties) - Method in interface smile.classification.DataFrameClassifier.Trainer

Fits a classification model.

fit(Formula, DataFrame, Properties) - Static method in class smile.classification.DecisionTree

Fits a classification tree.

fit(Formula, DataFrame, Properties) - Static method in class smile.classification.GradientTreeBoost

Fits a gradient tree boosting for classification.

fit(Formula, DataFrame, Properties) - Static method in class smile.classification.RandomForest

Fits a random forest for classification.

fit(Formula, DataFrame, Properties) - Method in interface smile.regression.DataFrameRegression.Trainer

Fits a regression model.

fit(Formula, DataFrame, Properties) - Static method in class smile.regression.ElasticNet

Fits an Elastic Net model.

fit(Formula, DataFrame, Properties) - Static method in class smile.regression.GradientTreeBoost

Fits a gradient tree boosting for regression.

fit(Formula, DataFrame, Properties) - Static method in class smile.regression.LASSO

Fits a L1-regularized least squares model.

fit(Formula, DataFrame, Properties) - Static method in class smile.regression.OLS

Fits an ordinary least squares model.

fit(Formula, DataFrame, Properties) - Static method in class smile.regression.RandomForest

Fits a random forest for regression.

fit(Formula, DataFrame, Properties) - Static method in class smile.regression.RegressionTree

Fits a regression tree.

fit(Formula, DataFrame, Properties) - Static method in class smile.regression.RidgeRegression

Fits a ridge regression model.

fit(Formula, DataFrame, Loss, int, int, int, int, double, double) - Static method in class smile.regression.GradientTreeBoost

Fits a gradient tree boosting for regression.

fit(Formula, DataFrame, SplitRule, int, int, int) - Static method in class smile.classification.DecisionTree

Fits a classification tree.

fit(Formula, DataFrame, Model) - Static method in class smile.glm.GLM

Fits the generalized linear model with IWLS (iteratively reweighted least squares).

fit(Formula, DataFrame, Model, double, int) - Static method in class smile.glm.GLM

Fits the generalized linear model with IWLS (iteratively reweighted least squares).

fit(Formula, DataFrame, Model, Properties) - Static method in class smile.glm.GLM

Fits the generalized linear model with IWLS (iteratively reweighted least squares).

fit(SparseDataset<Integer>) - Static method in class smile.classification.SparseLogisticRegression

Fits logistic regression.

fit(SparseDataset<Integer>, double, double, int) - Static method in class smile.classification.SparseLogisticRegression

Fits logistic regression.

fit(SparseDataset<Integer>, Properties) - Static method in class smile.classification.SparseLogisticRegression

Fits logistic regression.

fit(Tuple[][], int[][]) - Static method in class smile.sequence.CRF

Fits a CRF model.

fit(Tuple[][], int[][], int, int, int, int, double) - Static method in class smile.sequence.CRF

Fits a CRF model.

fit(Tuple[][], int[][], Properties) - Static method in class smile.sequence.CRF

Fits a CRF model.

fit(BaseVector<?, ?, ?>) - Static method in class smile.classification.ClassLabels

Fits the class label mapping.

fit(DifferentiableMultivariateFunction, double[][], double[], double[]) - Static method in class smile.math.LevenbergMarquardt

Fits the nonlinear least squares.

fit(DifferentiableMultivariateFunction, double[][], double[], double[], double, int) - Static method in class smile.math.LevenbergMarquardt

Fits the nonlinear least squares.

fit(DifferentiableMultivariateFunction, double[], double[], double[]) - Static method in class smile.math.LevenbergMarquardt

Fits the nonlinear least squares.

fit(DifferentiableMultivariateFunction, double[], double[], double[], double, int) - Static method in class smile.math.LevenbergMarquardt

Fits the nonlinear least squares.

fit(Matrix, int) - Static method in class smile.clustering.SpectralClustering

Spectral graph clustering.

fit(Matrix, int, int, double) - Static method in class smile.clustering.SpectralClustering

Spectral graph clustering.

fit(RNNSearch<double[], double[]>, double[][], double) - Method in class smile.neighbor.MPLSH

Fits the posteriori multiple probe algorithm.

fit(RNNSearch<double[], double[]>, double[][], double, int) - Method in class smile.neighbor.MPLSH

Fits the posteriori multiple probe algorithm.

fit(RNNSearch<double[], double[]>, double[][], double, int, double) - Method in class smile.neighbor.MPLSH

Train the posteriori multiple probe algorithm.

fit(SparseArray[], double[], int, double, double, double) - Static method in class smile.regression.SVM

Fits a linear epsilon-SVR of sparse data.

fit(SparseArray[], int) - Static method in class smile.clustering.SIB

Clustering data into k clusters up to 100 iterations.

fit(SparseArray[], int[], int, double, double) - Static method in class smile.classification.SVM

Fits a binary linear SVM.

fit(SparseArray[], int[], int, double, double, int) - Static method in class smile.classification.SVM

Fits a binary linear SVM.

fit(SparseArray[], int, int) - Static method in class smile.clustering.SIB

Clustering data into k clusters.

fit(T[]) - Method in class smile.base.svm.OCSVM

Fits an one-class support vector machine.

fit(T[][], int[][], Function<T, Tuple>) - Static method in class smile.sequence.CRFLabeler

Fits a CRF model.

fit(T[][], int[][], Function<T, Tuple>, int, int, int, int, double) - Static method in class smile.sequence.CRFLabeler

Fits a CRF.

fit(T[][], int[][], Function<T, Tuple>, Properties) - Static method in class smile.sequence.CRFLabeler

Fits a CRF model.

fit(T[][], int[][], ToIntFunction<T>) - Static method in class smile.sequence.HMM

Fits an HMM by maximum likelihood estimation.

fit(T[][], int[][], ToIntFunction<T>) - Static method in class smile.sequence.HMMLabeler

Fits an HMM by maximum likelihood estimation.

fit(T[], double[]) - Method in class smile.base.svm.SVR

Fits an epsilon support vector regression model.

fit(T[], double[]) - Method in interface smile.regression.Regression.Trainer

Fits a regression model with the default hyper-parameters.

fit(T[], double[], Properties) - Method in interface smile.regression.Regression.Trainer

Fits a regression model.

fit(T[], double[], RBF<T>[]) - Static method in class smile.regression.RBFNetwork

Fits a RBF network.

fit(T[], double[], RBF<T>[], boolean) - Static method in class smile.regression.RBFNetwork

Fits a RBF network.

fit(T[], double[], MercerKernel<T>, double) - Static method in class smile.regression.GaussianProcessRegression

Fits a regular Gaussian process model by the method of subset of regressors.

fit(T[], double[], MercerKernel<T>, double, boolean, double, int) - Static method in class smile.regression.GaussianProcessRegression

Fits a regular Gaussian process model.

fit(T[], double[], MercerKernel<T>, double, double, double) - Static method in class smile.regression.SVM

Fits an epsilon-SVR.

fit(T[], double[], MercerKernel<T>, Properties) - Static method in class smile.regression.GaussianProcessRegression

Fits a regular Gaussian process model.

fit(T[], double[], T[], MercerKernel<T>, double) - Static method in class smile.regression.GaussianProcessRegression

Fits an approximate Gaussian process model by the method of subset of regressors.

fit(T[], double[], T[], MercerKernel<T>, double, boolean) - Static method in class smile.regression.GaussianProcessRegression

Fits an approximate Gaussian process model by the method of subset of regressors.

fit(T[], double[], T[], MercerKernel<T>, Properties) - Static method in class smile.regression.GaussianProcessRegression

Fits an approximate Gaussian process model by the method of subset of regressors.

fit(T[], int[]) - Method in interface smile.classification.Classifier.Trainer

Fits a classification model with the default hyper-parameters.

fit(T[], int[], int) - Method in class smile.base.svm.LASVM

Trains the model.

fit(T[], int[], int, int, BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.classification.OneVersusOne

Fits a multi-class model with binary classifiers.

fit(T[], int[], int, int, BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.classification.OneVersusRest

Fits a multi-class model with binary classifiers.

fit(T[], int[], int, Distance<T>) - Static method in class smile.classification.KNN

Fits the K-NN classifier.

fit(T[], int[], BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.classification.OneVersusOne

Fits a multi-class model with binary classifiers.

fit(T[], int[], BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.classification.OneVersusRest

Fits a multi-class model with binary classifiers.

fit(T[], int[], Properties) - Method in interface smile.classification.Classifier.Trainer

Fits a classification model.

fit(T[], int[], RBF<T>[]) - Static method in class smile.classification.RBFNetwork

Fits a RBF network.

fit(T[], int[], RBF<T>[], boolean) - Static method in class smile.classification.RBFNetwork

Fits a RBF network.

fit(T[], int[], Distance<T>) - Static method in class smile.classification.KNN

Fits the 1-NN classifier.

fit(T[], int[], MercerKernel<T>, double, double) - Static method in class smile.classification.SVM

Fits a binary SVM.

fit(T[], int[], MercerKernel<T>, double, double, int) - Static method in class smile.classification.SVM

Fits a binary SVM.

fit(T[], Distance<T>, int) - Static method in class smile.clustering.CLARANS

Clustering data into k clusters.

fit(T[], Distance<T>, int, double) - Static method in class smile.clustering.DBSCAN

Clustering the data.

fit(T[], Distance<T>, int, double) - Static method in class smile.clustering.MEC

Clustering the data.

fit(T[], Distance<T>, int, int) - Static method in class smile.clustering.CLARANS

Constructor.

fit(T[], Metric<T>, int) - Static method in class smile.base.rbf.RBF

Fits Gaussian RBF function and centers on data.

fit(T[], Metric<T>, int, double) - Static method in class smile.base.rbf.RBF

Fits Gaussian RBF function and centers on data.

fit(T[], Metric<T>, int, int) - Static method in class smile.base.rbf.RBF

Fits Gaussian RBF function and centers on data.

fit(T[], MercerKernel<T>) - Static method in class smile.anomaly.SVM

Fits an one-class SVM.

fit(T[], MercerKernel<T>, double, double) - Static method in class smile.anomaly.SVM

Fits an one-class SVM.

fit(T[], MercerKernel<T>, int) - Static method in class smile.manifold.KPCA

Fits kernel principal component analysis.

fit(T[], MercerKernel<T>, int, double) - Static method in class smile.manifold.KPCA

Fits kernel principal component analysis.

fit(T[], RNNSearch<T, T>, int, double) - Static method in class smile.clustering.DBSCAN

Clustering the data.

fit(T[], RNNSearch<T, T>, int, double, int[], double) - Static method in class smile.clustering.MEC

Clustering the data.

fitness() - Method in class smile.gap.BitString

fitness() - Method in interface smile.gap.Chromosome

Returns the fitness of chromosome.

fitness(double[][], double[], double[][], double[], RegressionMetric, BiFunction<double[][], double[], Regression<double[]>>) - Static method in class smile.feature.selection.GAFE

Returns the fitness of the regression model.

fitness(double[][], int[], double[][], int[], ClassificationMetric, BiFunction<double[][], int[], Classifier<double[]>>) - Static method in class smile.feature.selection.GAFE

Returns the fitness of the classification model.

fitness(String, DataFrame, DataFrame, ClassificationMetric, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in class smile.feature.selection.GAFE

Returns the fitness of the classification model.

fitness(String, DataFrame, DataFrame, RegressionMetric, BiFunction<Formula, DataFrame, DataFrameRegression>) - Static method in class smile.feature.selection.GAFE

Returns the fitness of the regression model.

Fitness<T> - Interface in smile.gap

A measure to evaluate the fitness of chromosomes.

fittedValues - Variable in class smile.math.LevenbergMarquardt

The fitted values.

fittedValues() - Method in class smile.glm.GLM

Returns the fitted mean values.

fittedValues() - Method in class smile.regression.LinearModel

Returns the fitted values.

fittedValues() - Method in class smile.timeseries.AR

Returns the fitted values.

fittedValues() - Method in class smile.timeseries.ARMA

Returns the fitted values.

fitTime - Variable in class smile.validation.ClassificationMetrics

The time in milliseconds of fitting the model.

fitTime - Variable in class smile.validation.RegressionMetrics

The time in milliseconds of fitting the model.

flatten() - Method in class smile.deep.tensor.Tensor

Flattens the tensor by reshaping it into a one-dimensional tensor.

flatten(int) - Method in class smile.deep.tensor.Tensor

Flattens the tensor by reshaping it into a one-dimensional tensor.

flatten(int, int) - Method in class smile.deep.tensor.Tensor

Flattens the tensor by reshaping it into a one-dimensional tensor.

flatten(String[], String[]) - Method in class smile.plot.vega.Transform

Adds a flatten transform.

FLD - Class in smile.classification

Fisher's linear discriminant.

FLD(double[], double[][], Matrix) - Constructor for class smile.classification.FLD

Constructor.

FLD(double[], double[][], Matrix, IntSet) - Constructor for class smile.classification.FLD

Constructor.

Float - Enum constant in enum class smile.data.type.DataType.ID

Float type ID.

FLOAT_DIGITS - Static variable in class smile.math.MathEx

The number of digits (in radix base) in the mantissa.

FLOAT_EPSILON - Static variable in class smile.math.MathEx

The machine precision for the float type, which is the difference between 1 and the smallest value greater than 1 that is representable for the float type.

FLOAT_MACHEP - Static variable in class smile.math.MathEx

The largest negative integer such that 1.0 + RADIX^MACHEP ≠ 1.0, except that machep is bounded below by -(DIGITS+3)

FLOAT_NEGEP - Static variable in class smile.math.MathEx

The largest negative integer such that 1.0 - RADIX^NEGEP ≠ 1.0, except that negeps is bounded below by -(DIGITS+3)

Float16 - Enum constant in enum class smile.deep.tensor.ScalarType

Half-precision floating-point number.

Float32 - Enum constant in enum class smile.deep.tensor.ScalarType

Single-precision floating-point number.

Float64 - Enum constant in enum class smile.deep.tensor.ScalarType

Double-precision floating-point number.

FloatArrayCellRenderer - Class in smile.swing.table

Float array renderer in JTable.

FloatArrayCellRenderer() - Constructor for class smile.swing.table.FloatArrayCellRenderer

Constructor.

FloatArrayType - Static variable in class smile.data.type.DataTypes

Float Array data type.

FloatConsumer - Interface in smile.math.matrix.fp32

Single precision matrix element stream consumer.

FloatHeapSelect - Class in smile.sort

This class tracks the smallest values seen thus far in a stream of values.

FloatHeapSelect(float[]) - Constructor for class smile.sort.FloatHeapSelect

Constructor.

FloatHeapSelect(int) - Constructor for class smile.sort.FloatHeapSelect

Constructor.

FloatObjectType - Static variable in class smile.data.type.DataTypes

Float Object data type.

FloatType - Class in smile.data.type

Float data type.

FloatType - Static variable in class smile.data.type.DataTypes

Float data type.

floatValue() - Method in class smile.deep.tensor.Tensor

Returns the float value when the tensor holds a single value.

floatVector(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

floatVector(int) - Method in class smile.data.IndexDataFrame

floatVector(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

floatVector(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

FloatVector - Interface in smile.data.vector

An immutable float vector.

floor(String) - Static method in interface smile.data.formula.Terms

The floor(x) term.

floor(Term) - Static method in interface smile.data.formula.Terms

The floor(x) term.

fold(String[], String[]) - Method in class smile.plot.vega.Transform

Adds a fold transform.

folder2Id - Static variable in interface smile.vision.ImageNet

The map from folder name to class id.

folder2Target - Static variable in interface smile.vision.ImageNet

The functor mapping folder name to class id.

folders - Static variable in interface smile.vision.ImageNet

Folder names in the same order of labels.

font(String) - Method in class smile.plot.vega.Config

Sets the default font for all text marks, titles, and labels.

FontCellEditor - Class in smile.swing.table

Font editor in JTable.

FontCellEditor() - Constructor for class smile.swing.table.FontCellEditor

Constructor.

FontCellRenderer - Class in smile.swing.table

Font renderer in JTable.

FontCellRenderer() - Constructor for class smile.swing.table.FontCellRenderer

Constructor.

FontCellRenderer(String) - Constructor for class smile.swing.table.FontCellRenderer

Constructor.

FontChooser - Class in smile.swing

The FontChooser class is a swing component for font selection with JFileChooser-like APIs.

FontChooser() - Constructor for class smile.swing.FontChooser

Constructs a FontChooser object.

FontChooser(String[]) - Constructor for class smile.swing.FontChooser

Constructs a FontChooser object using the given font size array.

forEachNonZero(int, int, DoubleConsumer) - Method in class smile.math.matrix.SparseMatrix

For each loop on non-zero elements.

forEachNonZero(int, int, FloatConsumer) - Method in class smile.math.matrix.fp32.SparseMatrix

For each loop on non-zero elements.

forEachNonZero(DoubleConsumer) - Method in class smile.math.matrix.SparseMatrix

For each loop on non-zero elements.

forecast() - Method in class smile.timeseries.AR

Returns 1-step ahead forecast.

forecast() - Method in class smile.timeseries.ARMA

Returns 1-step ahead forecast.

forecast(int) - Method in class smile.timeseries.AR

Returns l-step ahead forecast.

forecast(int) - Method in class smile.timeseries.ARMA

Returns l-step ahead forecast.

FOREST_GREEN - Static variable in interface smile.plot.swing.Palette

format(double) - Static method in interface smile.util.Strings

Returns the string representation of a floating number without trailing zeros.

format(double, boolean) - Static method in interface smile.util.Strings

Returns the string representation of a floating number.

format(float) - Static method in interface smile.util.Strings

Returns the string representation of a floating number without trailing zeros.

format(float, boolean) - Static method in interface smile.util.Strings

Returns the string representation of a floating number.

format(String) - Method in class smile.plot.vega.Axis

Sets the text format.

format(String) - Method in class smile.plot.vega.Data

Sets the format for parsing the data.

format(String) - Method in class smile.plot.vega.Legend

Sets the text format.

format(String, Map<String, String>) - Method in class smile.plot.vega.Data

Sets the format for parsing the data.

FormatConfig - Class in smile.plot.vega

These config properties define the default number and time formats for text marks as well as axes, headers, tooltip, and legends.

formatType(String) - Method in class smile.plot.vega.Axis

Sets the format type for labels.

formatType(String) - Method in class smile.plot.vega.Legend

Sets the format type for labels.

formula - Variable in class smile.base.cart.CART

The model formula.

formula - Variable in class smile.glm.GLM

The symbolic description of the model to be fitted.

formula() - Method in class smile.classification.AdaBoost

formula() - Method in interface smile.classification.DataFrameClassifier

Returns the formula associated with the model.

formula() - Method in class smile.classification.DecisionTree

Returns null if the tree is part of ensemble algorithm.

formula() - Method in class smile.classification.GradientTreeBoost

formula() - Method in class smile.classification.RandomForest

formula() - Method in interface smile.feature.importance.TreeSHAP

Returns the formula associated with the model.

formula() - Method in interface smile.regression.DataFrameRegression

Returns the model formula.

formula() - Method in class smile.regression.GradientTreeBoost

formula() - Method in class smile.regression.LinearModel

formula() - Method in class smile.regression.RandomForest

formula() - Method in class smile.regression.RegressionTree

Returns null if the tree is part of ensemble algorithm.

Formula - Class in smile.data.formula

The model fitting formula in a compact symbolic form.

Formula(Term, Term...) - Constructor for class smile.data.formula.Formula

Constructor.

forward(BufferedImage...) - Method in interface smile.vision.transform.Transform

Transforms images to 4-D tensor with shape [samples, channels, height, width].

forward(BufferedImage...) - Method in class smile.vision.VisionModel

Forward propagation (or forward pass) through the model.

forward(Tensor) - Method in class smile.deep.activation.GELU

forward(Tensor) - Method in class smile.deep.activation.GLU

forward(Tensor) - Method in class smile.deep.activation.HardShrink

forward(Tensor) - Method in class smile.deep.activation.LeakyReLU

forward(Tensor) - Method in class smile.deep.activation.LogSigmoid

forward(Tensor) - Method in class smile.deep.activation.LogSoftmax

forward(Tensor) - Method in class smile.deep.activation.ReLU

forward(Tensor) - Method in class smile.deep.activation.Sigmoid

forward(Tensor) - Method in class smile.deep.activation.SiLU

forward(Tensor) - Method in class smile.deep.activation.Softmax

forward(Tensor) - Method in class smile.deep.activation.SoftShrink

forward(Tensor) - Method in class smile.deep.activation.Tanh

forward(Tensor) - Method in class smile.deep.activation.TanhShrink

forward(Tensor) - Method in class smile.deep.layer.AdaptiveAvgPool2dLayer

forward(Tensor) - Method in class smile.deep.layer.AvgPool2dLayer

forward(Tensor) - Method in class smile.deep.layer.BatchNorm1dLayer

forward(Tensor) - Method in class smile.deep.layer.BatchNorm2dLayer

forward(Tensor) - Method in class smile.deep.layer.Conv2dLayer

forward(Tensor) - Method in class smile.deep.layer.DropoutLayer

forward(Tensor) - Method in class smile.deep.layer.EmbeddingLayer

forward(Tensor) - Method in class smile.deep.layer.FullyConnectedLayer

forward(Tensor) - Method in class smile.deep.layer.GroupNormLayer

forward(Tensor) - Method in interface smile.deep.layer.Layer

Forward propagation (or forward pass) through the layer.

forward(Tensor) - Method in class smile.deep.layer.MaxPool2dLayer

forward(Tensor) - Method in class smile.deep.layer.SequentialBlock

forward(Tensor) - Method in class smile.deep.Model

Forward propagation (or forward pass) through the model.

forward(Tensor) - Method in class smile.llm.PositionalEncoding

forward(Tensor) - Method in class smile.llm.Transformer

Forward propagation (or forward pass).

forward(Tensor) - Method in class smile.vision.EfficientNet

forward(Tensor) - Method in class smile.vision.layer.Conv2dNormActivation

forward(Tensor) - Method in class smile.vision.layer.FusedMBConv

forward(Tensor) - Method in class smile.vision.layer.MBConv

forward(Tensor) - Method in class smile.vision.layer.SqueezeExcitation

forward(Tensor) - Method in class smile.vision.layer.StochasticDepth

FPGrowth - Class in smile.association

Frequent item set mining based on the FP-growth (frequent pattern growth) algorithm, which employs an extended prefix-tree (FP-tree) structure to store the database in a compressed form.

FPTree - Class in smile.association

FP-tree data structure used in FP-growth (frequent pattern growth) algorithm for frequent item set mining.

frame(Integer, Integer) - Method in class smile.plot.vega.ImputeTransform

Sets the frame to control the window over which the specified method is applied.

frame(Integer, Integer) - Method in class smile.plot.vega.WindowTransform

Sets the frame specification indicating how the sliding window should proceed.

frame(DataFrame) - Method in class smile.data.formula.Formula

Returns a data frame of predictors and optionally response variable (if input data frame has the related variable(s)).

from(Path) - Static method in interface smile.data.BinarySparseDataset

Parse a binary sparse dataset from a file, of which each line is a data item which are the indices of nonzero elements.

from(Path) - Static method in interface smile.data.SparseDataset

Parses spare dataset in coordinate triple tuple list format.

from(Path, int) - Static method in interface smile.data.SparseDataset

Reads spare dataset in coordinate triple tuple list format.

FScore - Class in smile.validation.metric

The F-score (or F-measure) considers both the precision and the recall of the test to compute the score.

FScore() - Constructor for class smile.validation.metric.FScore

Constructor of F1 score.

FScore(double) - Constructor for class smile.validation.metric.FScore

Constructor of general F-score.

ftest() - Method in class smile.regression.LinearModel

Returns the F-statistic of goodness-of-fit.

FTest - Class in smile.stat.hypothesis

F test of the hypothesis that two independent samples come from normal distributions with the same variance, against the alternative that they come from normal distributions with different variances.

FTest(double, int, int, double) - Constructor for class smile.stat.hypothesis.FTest

Constructor.

FullyConnectedLayer - Class in smile.deep.layer

A fully connected layer with nonlinear activation function.

FullyConnectedLayer(int, int) - Constructor for class smile.deep.layer.FullyConnectedLayer

Constructor.

Function - Interface in smile.math

An interface representing a univariate real function.

FusedMBConv - Class in smile.vision.layer

Fused-MBConv replaces the depthwise-conv3×3 and expansion-conv1×1 in MBConv with single regular conv3×3.

FusedMBConv(MBConvConfig, double, IntFunction<Layer>) - Constructor for class smile.vision.layer.FusedMBConv

Constructor.

FusedMBConv(double, int, int, int, int, int) - Static method in record class smile.vision.layer.MBConvConfig

Returns the config for Fused-MBConv block.

FW - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Foreign word.

G

g(double) - Method in class smile.ica.Exp

g(double) - Method in class smile.ica.Kurtosis

g(double) - Method in class smile.ica.LogCosh

g(double) - Method in interface smile.math.DifferentiableFunction

Computes the gradient/derivative at x.

g(double[], double[]) - Method in interface smile.base.mlp.activation.ActivationFunction

The gradient function.

g(double[], double[]) - Method in class smile.base.mlp.activation.LeakyReLU

g(double[], double[]) - Method in class smile.base.mlp.activation.ReLU

g(double[], double[]) - Method in class smile.base.mlp.activation.Sigmoid

g(double[], double[]) - Method in class smile.base.mlp.activation.Softmax

g(double[], double[]) - Method in class smile.base.mlp.activation.Tanh

g(double[], double[]) - Method in interface smile.base.mlp.ActivationFunction

The gradient function.

g(double[], double[]) - Method in interface smile.math.DifferentiableMultivariateFunction

Computes the value and gradient at x.

g(Cost, double[], double[]) - Method in enum class smile.base.mlp.OutputFunction

The gradient function.

g2(double) - Method in class smile.ica.Exp

g2(double) - Method in class smile.ica.Kurtosis

g2(double) - Method in class smile.ica.LogCosh

g2(double) - Method in interface smile.math.DifferentiableFunction

Compute the second-order derivative at x.

GAFE - Class in smile.feature.selection

Genetic algorithm based feature selection.

GAFE() - Constructor for class smile.feature.selection.GAFE

Constructor.

GAFE(Selection, int, Crossover, double, double) - Constructor for class smile.feature.selection.GAFE

Constructor.

gamma(double) - Static method in class smile.math.special.Gamma

Gamma function.

Gamma - Class in smile.math.special

The gamma, digamma, and incomplete gamma functions.

GammaDistribution - Class in smile.stat.distribution

The Gamma distribution is a continuous probability distributions with a scale parameter θ and a shape parameter k.

GammaDistribution(double, double) - Constructor for class smile.stat.distribution.GammaDistribution

Constructor.

gather(int, Tensor) - Method in class smile.deep.tensor.Tensor

Gathers values along an axis specified by dim.

Gaussian - Class in smile.math.kernel

Gaussian kernel, also referred as RBF kernel or squared exponential kernel.

Gaussian(double, double, double) - Constructor for class smile.math.kernel.Gaussian

Constructor.

Gaussian(double, double) - Static method in interface smile.vq.Neighborhood

Returns Gaussian neighborhood function.

GaussianDistribution - Class in smile.stat.distribution

The normal distribution or Gaussian distribution is a continuous probability distribution that describes data that clusters around a mean.

GaussianDistribution(double, double) - Constructor for class smile.stat.distribution.GaussianDistribution

Constructor

GaussianKernel - Class in smile.math.kernel

Gaussian kernel, also referred as RBF kernel or squared exponential kernel.

GaussianKernel(double) - Constructor for class smile.math.kernel.GaussianKernel

Constructor.

GaussianKernel(double, double, double) - Constructor for class smile.math.kernel.GaussianKernel

Constructor.

GaussianMixture - Class in smile.stat.distribution

Finite univariate Gaussian mixture.

GaussianMixture(Mixture.Component...) - Constructor for class smile.stat.distribution.GaussianMixture

Constructor.

GaussianProcessRegression<T> - Class in smile.regression

Gaussian Process for Regression.

GaussianProcessRegression(MercerKernel<T>, T[], double[], double) - Constructor for class smile.regression.GaussianProcessRegression

Constructor.

GaussianProcessRegression(MercerKernel<T>, T[], double[], double, double, double) - Constructor for class smile.regression.GaussianProcessRegression

Constructor.

GaussianProcessRegression(MercerKernel<T>, T[], double[], double, double, double, Matrix.Cholesky, double) - Constructor for class smile.regression.GaussianProcessRegression

Constructor.

GaussianProcessRegression.JointPrediction - Class in smile.regression

The joint prediction of multiple data points.

GaussianRadialBasis - Class in smile.math.rbf

Gaussian RBF.

GaussianRadialBasis() - Constructor for class smile.math.rbf.GaussianRadialBasis

Constructor.

GaussianRadialBasis(double) - Constructor for class smile.math.rbf.GaussianRadialBasis

Constructor.

GaussianVariogram - Class in smile.interpolation.variogram

Gaussian variogram.

GaussianVariogram(double, double) - Constructor for class smile.interpolation.variogram.GaussianVariogram

Constructor.

GaussianVariogram(double, double, double) - Constructor for class smile.interpolation.variogram.GaussianVariogram

Constructor.

gbmv(Layout, Transpose, int, int, int, int, double, double[], int, double[], int, double, double[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a band matrix.

gbmv(Layout, Transpose, int, int, int, int, double, double[], int, double[], int, double, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gbmv(Layout, Transpose, int, int, int, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a band matrix.

gbmv(Layout, Transpose, int, int, int, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gbmv(Layout, Transpose, int, int, int, int, float, float[], int, float[], int, float, float[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a band matrix.

gbmv(Layout, Transpose, int, int, int, int, float, float[], int, float[], int, float, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gbmv(Layout, Transpose, int, int, int, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a band matrix.

gbmv(Layout, Transpose, int, int, int, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gbsv(Layout, int, int, int, int, double[], int, int[], double[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

gbsv(Layout, int, int, int, int, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gbsv(Layout, int, int, int, int, float[], int, int[], float[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

gbsv(Layout, int, int, int, int, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gbsv(Layout, int, int, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

gbsv(Layout, int, int, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gbsv(Layout, int, int, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

gbsv(Layout, int, int, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gbtrf(Layout, int, int, int, int, double[], int, int[]) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a band matrix A using partial pivoting with row interchanges.

gbtrf(Layout, int, int, int, int, double[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

gbtrf(Layout, int, int, int, int, float[], int, int[]) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a band matrix A using partial pivoting with row interchanges.

gbtrf(Layout, int, int, int, int, float[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

gbtrf(Layout, int, int, int, int, DoubleBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a band matrix A using partial pivoting with row interchanges.

gbtrf(Layout, int, int, int, int, DoubleBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gbtrf(Layout, int, int, int, int, FloatBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a band matrix A using partial pivoting with row interchanges.

gbtrf(Layout, int, int, int, int, FloatBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gbtrs(Layout, Transpose, int, int, int, int, double[], int, int[], double[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

gbtrs(Layout, Transpose, int, int, int, int, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gbtrs(Layout, Transpose, int, int, int, int, float[], int, int[], float[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

gbtrs(Layout, Transpose, int, int, int, int, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gbtrs(Layout, Transpose, int, int, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

gbtrs(Layout, Transpose, int, int, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gbtrs(Layout, Transpose, int, int, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

gbtrs(Layout, Transpose, int, int, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

ge(double) - Method in class smile.deep.tensor.Tensor

Computes element-wise greater-than-or-equal-to comparison.

ge(int) - Method in class smile.deep.tensor.Tensor

Computes element-wise greater-than-or-equal-to comparison.

ge(Tensor) - Method in class smile.deep.tensor.Tensor

Computes element-wise greater-than-or-equal-to comparison.

geev(Layout, EVDJob, EVDJob, int, double[], int, double[], double[], double[], int, double[], int) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors.

geev(Layout, EVDJob, EVDJob, int, double[], int, double[], double[], double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

geev(Layout, EVDJob, EVDJob, int, float[], int, float[], float[], float[], int, float[], int) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors.

geev(Layout, EVDJob, EVDJob, int, float[], int, float[], float[], float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

geev(Layout, EVDJob, EVDJob, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors.

geev(Layout, EVDJob, EVDJob, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

geev(Layout, EVDJob, EVDJob, int, FloatBuffer, int, FloatBuffer, FloatBuffer, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors.

geev(Layout, EVDJob, EVDJob, int, FloatBuffer, int, FloatBuffer, FloatBuffer, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

geev(Layout, EVDJob, EVDJob, int, DoublePointer, int, DoublePointer, DoublePointer, DoublePointer, int, DoublePointer, int) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors.

geev(Layout, EVDJob, EVDJob, int, DoublePointer, int, DoublePointer, DoublePointer, DoublePointer, int, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gels(Layout, Transpose, int, int, int, double[], int, double[], int) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a QR or LQ factorization of A.

gels(Layout, Transpose, int, int, int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gels(Layout, Transpose, int, int, int, float[], int, float[], int) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a QR or LQ factorization of A.

gels(Layout, Transpose, int, int, int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gels(Layout, Transpose, int, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a QR or LQ factorization of A.

gels(Layout, Transpose, int, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gels(Layout, Transpose, int, int, int, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a QR or LQ factorization of A.

gels(Layout, Transpose, int, int, int, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gelsd(Layout, int, int, int, double[], int, double[], int, double[], double, int[]) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a divide and conquer algorithm with the singular value decomposition (SVD) of A.

gelsd(Layout, int, int, int, double[], int, double[], int, double[], double, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

gelsd(Layout, int, int, int, float[], int, float[], int, float[], float, int[]) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a divide and conquer algorithm with the singular value decomposition (SVD) of A.

gelsd(Layout, int, int, int, float[], int, float[], int, float[], float, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

gelsd(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, double, IntBuffer) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a divide and conquer algorithm with the singular value decomposition (SVD) of A.

gelsd(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, double, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gelsd(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, FloatBuffer, float, IntBuffer) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a divide and conquer algorithm with the singular value decomposition (SVD) of A.

gelsd(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, FloatBuffer, float, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gelss(Layout, int, int, int, double[], int, double[], int, double[], double, int[]) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using the singular value decomposition (SVD) of A.

gelss(Layout, int, int, int, double[], int, double[], int, double[], double, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

gelss(Layout, int, int, int, float[], int, float[], int, float[], float, int[]) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using the singular value decomposition (SVD) of A.

gelss(Layout, int, int, int, float[], int, float[], int, float[], float, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

gelss(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, double, IntBuffer) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using the singular value decomposition (SVD) of A.

gelss(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, double, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gelss(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, FloatBuffer, float, IntBuffer) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using the singular value decomposition (SVD) of A.

gelss(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, FloatBuffer, float, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gelsy(Layout, int, int, int, double[], int, double[], int, int[], double, int[]) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a complete orthogonal factorization of A.

gelsy(Layout, int, int, int, double[], int, double[], int, int[], double, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

gelsy(Layout, int, int, int, float[], int, float[], int, int[], float, int[]) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a complete orthogonal factorization of A.

gelsy(Layout, int, int, int, float[], int, float[], int, int[], float, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

gelsy(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer, int, IntBuffer, double, IntBuffer) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a complete orthogonal factorization of A.

gelsy(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer, int, IntBuffer, double, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gelsy(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, IntBuffer, float, IntBuffer) - Method in interface smile.math.blas.LAPACK

Solves an overdetermined or underdetermined system, using a complete orthogonal factorization of A.

gelsy(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, IntBuffer, float, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gelu(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with GELU activation function.

gelu(int, int, double) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with GELU activation function.

GELU - Class in smile.deep.activation

Gaussian Error Linear Unit activation function.

GELU(boolean) - Constructor for class smile.deep.activation.GELU

Constructor.

gemm(Layout, Transpose, Transpose, int, int, int, double, double[], int, double[], int, double, double[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-matrix operation.

gemm(Layout, Transpose, Transpose, int, int, int, double, double[], int, double[], int, double, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gemm(Layout, Transpose, Transpose, int, int, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-matrix operation.

gemm(Layout, Transpose, Transpose, int, int, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gemm(Layout, Transpose, Transpose, int, int, int, double, DoublePointer, int, DoublePointer, int, double, DoublePointer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-matrix operation.

gemm(Layout, Transpose, Transpose, int, int, int, double, DoublePointer, int, DoublePointer, int, double, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gemm(Layout, Transpose, Transpose, int, int, int, float, float[], int, float[], int, float, float[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-matrix operation.

gemm(Layout, Transpose, Transpose, int, int, int, float, float[], int, float[], int, float, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gemm(Layout, Transpose, Transpose, int, int, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-matrix operation.

gemm(Layout, Transpose, Transpose, int, int, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gemv(Layout, Transpose, int, int, double, double[], int, double[], int, double, double[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation.

gemv(Layout, Transpose, int, int, double, double[], int, double[], int, double, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gemv(Layout, Transpose, int, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation.

gemv(Layout, Transpose, int, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gemv(Layout, Transpose, int, int, double, DoublePointer, int, DoublePointer, int, double, DoublePointer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation.

gemv(Layout, Transpose, int, int, double, DoublePointer, int, DoublePointer, int, double, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gemv(Layout, Transpose, int, int, float, float[], int, float[], int, float, float[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation.

gemv(Layout, Transpose, int, int, float, float[], int, float[], int, float, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gemv(Layout, Transpose, int, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation.

gemv(Layout, Transpose, int, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

generateSeed() - Static method in class smile.math.MathEx

Returns a random number to seed other random number generators.

generateSeed(int) - Static method in class smile.math.MathEx

Returns the given number of random bytes to seed other random number generators.

GeneticAlgorithm<T> - Class in smile.gap

A genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution.

GeneticAlgorithm(T[]) - Constructor for class smile.gap.GeneticAlgorithm

Constructor.

GeneticAlgorithm(T[], Selection, int) - Constructor for class smile.gap.GeneticAlgorithm

Constructor.

GeometricDistribution - Class in smile.stat.distribution

The geometric distribution is a discrete probability distribution of the number X of Bernoulli trials needed to get one success, supported on the set {1, 2, 3, …}.

GeometricDistribution(double) - Constructor for class smile.stat.distribution.GeometricDistribution

Constructor.

geqrf(Layout, int, int, double[], int, double[]) - Method in interface smile.math.blas.LAPACK

Computes a QR factorization of a general M-by-N matrix A.

geqrf(Layout, int, int, double[], int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS

geqrf(Layout, int, int, float[], int, float[]) - Method in interface smile.math.blas.LAPACK

Computes a QR factorization of a general M-by-N matrix A.

geqrf(Layout, int, int, float[], int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS

geqrf(Layout, int, int, DoubleBuffer, int, DoubleBuffer) - Method in interface smile.math.blas.LAPACK

Computes a QR factorization of a general M-by-N matrix A.

geqrf(Layout, int, int, DoubleBuffer, int, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

geqrf(Layout, int, int, FloatBuffer, int, FloatBuffer) - Method in interface smile.math.blas.LAPACK

Computes a QR factorization of a general M-by-N matrix A.

geqrf(Layout, int, int, FloatBuffer, int, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

geqrf(Layout, int, int, DoublePointer, int, DoublePointer) - Method in interface smile.math.blas.LAPACK

Computes a QR factorization of a general M-by-N matrix A.

geqrf(Layout, int, int, DoublePointer, int, DoublePointer) - Method in class smile.math.blas.openblas.OpenBLAS

ger(Layout, int, int, double, double[], int, double[], int, double[], int) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation.

ger(Layout, int, int, double, double[], int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

ger(Layout, int, int, double, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation.

ger(Layout, int, int, double, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

ger(Layout, int, int, double, DoublePointer, int, DoublePointer, int, DoublePointer, int) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation.

ger(Layout, int, int, double, DoublePointer, int, DoublePointer, int, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

ger(Layout, int, int, float, float[], int, float[], int, float[], int) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation.

ger(Layout, int, int, float, float[], int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

ger(Layout, int, int, float, FloatBuffer, int, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation.

ger(Layout, int, int, float, FloatBuffer, int, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gesdd(Layout, SVDJob, int, int, double[], int, double[], double[], int, double[], int) - Method in interface smile.math.blas.LAPACK

Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.

gesdd(Layout, SVDJob, int, int, double[], int, double[], double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gesdd(Layout, SVDJob, int, int, float[], int, float[], float[], int, float[], int) - Method in interface smile.math.blas.LAPACK

Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.

gesdd(Layout, SVDJob, int, int, float[], int, float[], float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gesdd(Layout, SVDJob, int, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.

gesdd(Layout, SVDJob, int, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gesdd(Layout, SVDJob, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.

gesdd(Layout, SVDJob, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gesdd(Layout, SVDJob, int, int, DoublePointer, int, DoublePointer, DoublePointer, int, DoublePointer, int) - Method in interface smile.math.blas.LAPACK

Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.

gesdd(Layout, SVDJob, int, int, DoublePointer, int, DoublePointer, DoublePointer, int, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gesv(Layout, int, int, double[], int, int[], double[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

gesv(Layout, int, int, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gesv(Layout, int, int, float[], int, int[], float[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

gesv(Layout, int, int, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

gesv(Layout, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

gesv(Layout, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gesv(Layout, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

gesv(Layout, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gesv(Layout, int, int, DoublePointer, int, IntPointer, DoublePointer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

gesv(Layout, int, int, DoublePointer, int, IntPointer, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

gesvd(Layout, SVDJob, SVDJob, int, int, double[], int, double[], double[], int, double[], int, double[]) - Method in interface smile.math.blas.LAPACK

Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.

gesvd(Layout, SVDJob, SVDJob, int, int, double[], int, double[], double[], int, double[], int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS

gesvd(Layout, SVDJob, SVDJob, int, int, float[], int, float[], float[], int, float[], int, float[]) - Method in interface smile.math.blas.LAPACK

Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.

gesvd(Layout, SVDJob, SVDJob, int, int, float[], int, float[], float[], int, float[], int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS

gesvd(Layout, SVDJob, SVDJob, int, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer) - Method in interface smile.math.blas.LAPACK

Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.

gesvd(Layout, SVDJob, SVDJob, int, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gesvd(Layout, SVDJob, SVDJob, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int, FloatBuffer, int, FloatBuffer) - Method in interface smile.math.blas.LAPACK

Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.

gesvd(Layout, SVDJob, SVDJob, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int, FloatBuffer, int, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

get(double[]) - Method in class smile.neighbor.lsh.Hash

Returns the bucket entry for the given point.

get(int) - Method in interface smile.data.DataFrame

Returns the row at the specified index.

get(int) - Method in interface smile.data.Dataset

Returns the instance at the specified index.

get(int) - Method in class smile.data.IndexDataFrame

get(int) - Method in interface smile.data.Tuple

Returns the value at position i.

get(int) - Method in interface smile.data.vector.BaseVector

Returns the value at position i, which may be null.

get(int) - Method in class smile.math.Complex.Array

Returns the i-th element.

get(int) - Method in class smile.math.matrix.fp32.SparseMatrix

Returns the element at the storage index.

get(int) - Method in class smile.math.matrix.SparseMatrix

Returns the element at the storage index.

get(int) - Method in class smile.neighbor.lsh.Hash

Returns the bucket entry for the given hash value.

get(int) - Method in class smile.sort.DoubleHeapSelect

Returns the i-th smallest value seen so far.

get(int) - Method in class smile.sort.FloatHeapSelect

Returns the i-th smallest value seen so far.

get(int) - Method in class smile.sort.HeapSelect

Returns the i-th smallest value seen so far.

get(int) - Method in class smile.sort.IntHeapSelect

Returns the i-th smallest value seen so far.

get(int) - Method in class smile.util.DoubleArrayList

Returns the value at the specified position in this list.

get(int) - Method in class smile.util.IntArrayList

Returns the value at the specified position in this list.

get(int) - Method in class smile.util.IntDoubleHashMap

Returns the value to which the specified key is mapped, or Double.NaN if this map contains no mapping for the key.

get(int) - Method in class smile.util.SparseArray

Returns the value of i-th entry.

get(int...) - Method in interface smile.data.vector.BaseVector

Returns a new vector with selected entries.

get(int...) - Method in interface smile.data.vector.BooleanVector

get(int...) - Method in interface smile.data.vector.ByteVector

get(int...) - Method in interface smile.data.vector.CharVector

get(int...) - Method in interface smile.data.vector.DoubleVector

get(int...) - Method in interface smile.data.vector.FloatVector

get(int...) - Method in interface smile.data.vector.IntVector

get(int...) - Method in interface smile.data.vector.LongVector

get(int...) - Method in interface smile.data.vector.ShortVector

get(int...) - Method in interface smile.data.vector.StringVector

get(int...) - Method in interface smile.data.vector.Vector

get(int...) - Method in class smile.deep.tensor.Tensor

Returns a portion of tensor given the indices.

get(int[], int[]) - Method in class smile.math.matrix.BigMatrix

Returns the matrix of selected rows and columns.

get(int[], int[]) - Method in class smile.math.matrix.fp32.Matrix

Returns the matrix of selected rows and columns.

get(int[], int[]) - Method in class smile.math.matrix.Matrix

Returns the matrix of selected rows and columns.

get(int, int) - Method in interface smile.data.BinarySparseDataset

Returns the binary value at entry (i, j) by binary search.

get(int, int) - Method in interface smile.data.DataFrame

Returns the cell at (i, j).

get(int, int) - Method in class smile.data.IndexDataFrame

get(int, int) - Method in interface smile.data.SparseDataset

Returns the value at entry (i, j).

get(int, int) - Method in class smile.math.matrix.BandMatrix

get(int, int) - Method in class smile.math.matrix.BigMatrix

get(int, int) - Method in class smile.math.matrix.fp32.BandMatrix

get(int, int) - Method in class smile.math.matrix.fp32.IMatrix

Returns A[i,j].

get(int, int) - Method in class smile.math.matrix.fp32.Matrix

get(int, int) - Method in class smile.math.matrix.fp32.SparseMatrix

get(int, int) - Method in class smile.math.matrix.fp32.SymmMatrix

get(int, int) - Method in class smile.math.matrix.IMatrix

Returns A[i,j].

get(int, int) - Method in class smile.math.matrix.Matrix

get(int, int) - Method in class smile.math.matrix.SparseMatrix

get(int, int) - Method in class smile.math.matrix.SymmMatrix

get(int, int) - Method in interface smile.plot.swing.Hexmap.Tooltip

Gets the tooltip of cell at (i, j).

get(int, int) - Method in class smile.util.Array2D

Returns A[i, j].

get(int, int) - Method in class smile.util.IntArray2D

Returns A[i, j].

get(int, String) - Method in interface smile.data.DataFrame

Returns the cell at (i, j).

get(long...) - Method in class smile.deep.tensor.Tensor

Returns a portion of tensor given the indices.

get(String) - Method in interface smile.data.Tuple

Returns the value by field name.

get(String) - Method in class smile.hash.PerfectHash

Returns the index of a keyword.

get(String) - Method in class smile.hash.PerfectMap

Returns the value associated with the key.

get(String) - Method in class smile.nlp.embedding.Word2Vec

Returns the embedding vector of a word.

get(String) - Static method in class smile.nlp.pos.EnglishPOSLexicon

Returns the part-of-speech tags for given word, or null if the word does not exist in the dictionary.

get(K) - Method in class smile.nlp.Trie

Returns the node of a given key.

get(K[]) - Method in class smile.nlp.Trie

Returns the associated value of a given key.

get(Index...) - Method in class smile.deep.tensor.Tensor

Returns a portion of tensor given the indices.

get(Tensor) - Method in class smile.deep.tensor.Tensor

Returns a portion of tensor given the indices.

getAbbreviation(String) - Method in interface smile.nlp.dictionary.Abbreviations

Returns the abbreviation for a word.

getAlpha() - Method in class smile.swing.AlphaIcon

Gets this AlphaIcon's opacity

getAnchor() - Method in interface smile.nlp.AnchorText

Returns the anchor text if any.

getAnchor() - Method in class smile.nlp.SimpleText

Returns the anchor text if any.

getArray(int) - Method in interface smile.data.Tuple

Returns the value at position i of array type.

getArray(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) of array type.

getArray(int, String) - Method in interface smile.data.DataFrame

Returns the field value of array type.

getArray(String) - Method in interface smile.data.Tuple

Returns the field value of array type.

getAs(int) - Method in interface smile.data.Tuple

Returns the value at position i.

getAs(String) - Method in interface smile.data.Tuple

Returns the value of a given fieldName.

getAxis(int) - Method in class smile.plot.swing.Canvas

Returns the i-th axis.

getAxisLabel(int) - Method in class smile.plot.swing.Canvas

Returns the label/legend of an axis.

getAxisLabels() - Method in class smile.plot.swing.Canvas

Returns the labels/legends of axes.

getBoolean(int) - Method in interface smile.data.Tuple

Returns the value at position i as a primitive boolean.

getBoolean(int) - Method in interface smile.data.vector.BaseVector

Returns the boolean value at position i.

getBoolean(int) - Method in interface smile.data.vector.ByteVector

getBoolean(int) - Method in interface smile.data.vector.CharVector

getBoolean(int) - Method in interface smile.data.vector.DoubleVector

getBoolean(int) - Method in interface smile.data.vector.FloatVector

getBoolean(int) - Method in interface smile.data.vector.IntVector

getBoolean(int) - Method in interface smile.data.vector.LongVector

getBoolean(int) - Method in interface smile.data.vector.ShortVector

getBoolean(int) - Method in interface smile.data.vector.StringVector

getBoolean(int) - Method in interface smile.data.vector.Vector

getBoolean(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) as a primitive boolean.

getBoolean(int, String) - Method in interface smile.data.DataFrame

Returns the field value as a primitive boolean.

getBoolean(String) - Method in interface smile.data.Tuple

Returns the field value as a primitive boolean.

getByte(int) - Method in interface smile.data.Tuple

Returns the value at position i as a primitive byte.

getByte(int) - Method in interface smile.data.vector.BaseVector

Returns the byte value at position i.

getByte(int) - Method in interface smile.data.vector.BooleanVector

getByte(int) - Method in interface smile.data.vector.CharVector

getByte(int) - Method in interface smile.data.vector.DoubleVector

getByte(int) - Method in interface smile.data.vector.FloatVector

getByte(int) - Method in interface smile.data.vector.IntVector

getByte(int) - Method in interface smile.data.vector.LongVector

getByte(int) - Method in interface smile.data.vector.ShortVector

getByte(int) - Method in interface smile.data.vector.StringVector

getByte(int) - Method in interface smile.data.vector.Vector

getByte(int...) - Method in class smile.deep.tensor.Tensor

Returns the byte value of element at given index.

getByte(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) as a primitive byte.

getByte(int, String) - Method in interface smile.data.DataFrame

Returns the field value as a primitive byte.

getByte(long...) - Method in class smile.deep.tensor.Tensor

Returns the byte value of element at given index.

getByte(String) - Method in interface smile.data.Tuple

Returns the field value as a primitive byte.

getCellEditor(int, int) - Method in class smile.swing.Table

getCellEditorValue() - Method in class smile.swing.table.ButtonCellRenderer

getCellEditorValue() - Method in class smile.swing.table.ColorCellEditor

getCellEditorValue() - Method in class smile.swing.table.DateCellEditor

getCellEditorValue() - Method in class smile.swing.table.DoubleArrayCellEditor

getCellEditorValue() - Method in class smile.swing.table.DoubleCellEditor

getCellEditorValue() - Method in class smile.swing.table.FontCellEditor

getCellEditorValue() - Method in class smile.swing.table.IntegerArrayCellEditor

getCellEditorValue() - Method in class smile.swing.table.IntegerCellEditor

getCellRenderer(int, int) - Method in class smile.swing.Table

getChar(int) - Method in interface smile.data.Tuple

Returns the value at position i as a primitive byte.

getChar(int) - Method in interface smile.data.vector.BaseVector

Returns the character value at position i.

getChar(int) - Method in interface smile.data.vector.BooleanVector

getChar(int) - Method in interface smile.data.vector.ByteVector

getChar(int) - Method in interface smile.data.vector.DoubleVector

getChar(int) - Method in interface smile.data.vector.FloatVector

getChar(int) - Method in interface smile.data.vector.IntVector

getChar(int) - Method in interface smile.data.vector.LongVector

getChar(int) - Method in interface smile.data.vector.ShortVector

getChar(int) - Method in interface smile.data.vector.StringVector

getChar(int) - Method in interface smile.data.vector.Vector

getChar(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) as a primitive byte.

getChar(int, String) - Method in interface smile.data.DataFrame

Returns the field value as a primitive byte.

getChar(String) - Method in interface smile.data.Tuple

Returns the field value as a primitive byte.

getChild(K) - Method in class smile.nlp.Trie.Node

Returns the child with the key.

getChild(K[], int) - Method in class smile.nlp.Trie.Node

Returns the value matching the key sequence.

getClipNorm() - Method in class smile.base.mlp.MultilayerPerceptron

Returns the gradient clipping norm.

getClipValue() - Method in class smile.base.mlp.MultilayerPerceptron

Returns the gradient clipping value.

getColor() - Method in class smile.plot.swing.Graphics

Get the current color.

getComponentType() - Method in class smile.data.type.ArrayType

Returns the type of array elements.

getConcept(String) - Method in class smile.taxonomy.Taxonomy

Returns the concept node which synset contains the keyword.

getConcepts() - Method in class smile.taxonomy.Taxonomy

Returns all named concepts in the taxonomy.

getCoordinateSpace() - Method in class smile.plot.swing.Base

Returns the coordinates.

getDate(int) - Method in interface smile.data.Tuple

Returns the value at position i of date type as java.time.LocalDate.

getDate(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) of date type as java.time.LocalDate.

getDate(int, String) - Method in interface smile.data.DataFrame

Returns the field value of date type as java.time.LocalDate.

getDate(String) - Method in interface smile.data.Tuple

Returns the field value of date type as java.time.LocalDate.

getDateTime(int) - Method in interface smile.data.Tuple

Returns the value at position i of date type as java.time.LocalDateTime.

getDateTime(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) as java.time.LocalDateTime.

getDateTime(int, String) - Method in interface smile.data.DataFrame

Returns the field value as java.time.LocalDateTime.

getDateTime(String) - Method in interface smile.data.Tuple

Returns the field value of date type as java.time.LocalDateTime.

getDecimal(int) - Method in interface smile.data.Tuple

Returns the value at position i of decimal type as java.math.BigDecimal.

getDecimal(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) of decimal type as java.math.BigDecimal.

getDecimal(int, String) - Method in interface smile.data.DataFrame

Returns the field value of decimal type as java.math.BigDecimal.

getDecimal(String) - Method in interface smile.data.Tuple

Returns the field value of decimal type as java.math.BigDecimal.

getDefault() - Static method in class smile.nlp.pos.HMMPOSTagger

Returns the default English POS tagger.

getDegree(int) - Method in class smile.graph.AdjacencyList

getDegree(int) - Method in class smile.graph.AdjacencyMatrix

getDegree(int) - Method in interface smile.graph.Graph

Returns the degree of the specified vertex.

getDescription() - Method in class smile.swing.FileChooser.SimpleFileFilter

Returns the human readable description of this filter.

getDimension() - Method in class smile.plot.swing.Base

Returns the dimensionality of coordinates.

getDouble(int) - Method in interface smile.data.Tuple

Returns the value at position i as a primitive double.

getDouble(int) - Method in interface smile.data.vector.BaseVector

Returns the double value at position i.

getDouble(int) - Method in interface smile.data.vector.BooleanVector

getDouble(int) - Method in interface smile.data.vector.ByteVector

getDouble(int) - Method in interface smile.data.vector.CharVector

getDouble(int) - Method in interface smile.data.vector.FloatVector

getDouble(int) - Method in interface smile.data.vector.IntVector

getDouble(int) - Method in interface smile.data.vector.LongVector

getDouble(int) - Method in interface smile.data.vector.ShortVector

getDouble(int) - Method in interface smile.data.vector.StringVector

getDouble(int) - Method in interface smile.data.vector.Vector

getDouble(int...) - Method in class smile.deep.tensor.Tensor

Returns the double value of element at given index.

getDouble(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) as a primitive double.

getDouble(int, String) - Method in interface smile.data.DataFrame

Returns the field value as a primitive double.

getDouble(long...) - Method in class smile.deep.tensor.Tensor

Returns the double value of element at given index.

getDouble(String) - Method in interface smile.data.Tuple

Returns the field value as a primitive double.

getEdge(int, int) - Method in class smile.graph.AdjacencyList

getEdge(int, int) - Method in class smile.graph.AdjacencyMatrix

getEdge(int, int) - Method in interface smile.graph.Graph

Returns an edge connecting source vertex to target vertex if such edge exist in this graph.

getEdges() - Method in class smile.graph.AdjacencyList

getEdges() - Method in class smile.graph.AdjacencyMatrix

getEdges() - Method in interface smile.graph.Graph

Returns the edges in this graph.

getEdges(int) - Method in class smile.graph.AdjacencyList

getEdges(int) - Method in class smile.graph.AdjacencyMatrix

getEdges(int) - Method in interface smile.graph.Graph

Returns the edges from the specified vertex.

getEdges(int, int) - Method in class smile.graph.AdjacencyList

getEdges(int, int) - Method in class smile.graph.AdjacencyMatrix

getEdges(int, int) - Method in interface smile.graph.Graph

Returns the edges connecting source vertex to target vertex if such vertices exist in this graph.

getExtension(File) - Static method in class smile.swing.FileChooser

Returns the file name extension in lower case.

getExtensionLevel() - Method in class smile.anomaly.IsolationForest

Returns the extension level.

getFloat(int) - Method in interface smile.data.Tuple

Returns the value at position i as a primitive float.

getFloat(int) - Method in interface smile.data.vector.BaseVector

Returns the float value at position i.

getFloat(int) - Method in interface smile.data.vector.BooleanVector

getFloat(int) - Method in interface smile.data.vector.ByteVector

getFloat(int) - Method in interface smile.data.vector.CharVector

getFloat(int) - Method in interface smile.data.vector.DoubleVector

getFloat(int) - Method in interface smile.data.vector.IntVector

getFloat(int) - Method in interface smile.data.vector.LongVector

getFloat(int) - Method in interface smile.data.vector.ShortVector

getFloat(int) - Method in interface smile.data.vector.StringVector

getFloat(int) - Method in interface smile.data.vector.Vector

getFloat(int...) - Method in class smile.deep.tensor.Tensor

Returns the float value of element at given index.

getFloat(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) as a primitive float.

getFloat(int, String) - Method in interface smile.data.DataFrame

Returns the field value as a primitive float.

getFloat(long...) - Method in class smile.deep.tensor.Tensor

Returns the float value of element at given index.

getFloat(String) - Method in interface smile.data.Tuple

Returns the field value as a primitive float.

getFocusBorder() - Method in class smile.swing.table.ButtonCellRenderer

Get foreground color of the button when the cell has focus

getFont() - Method in class smile.plot.swing.Graphics

Get the current font.

getFull(String) - Method in interface smile.nlp.dictionary.Abbreviations

Returns the full word of an abbreviation.

getGraphics() - Method in class smile.plot.swing.Graphics

Returns the Java2D graphics object.

getHeight() - Method in class smile.plot.swing.Dendrogram

Returns the height of tree.

getIcon() - Method in class smile.swing.AlphaIcon

Gets the icon wrapped by this AlphaIcon

getIcon(JTable, int) - Method in class smile.swing.table.DefaultTableHeaderCellRenderer

Overloaded to return an icon suitable to the primary sorted column, or null if the column is not the primary sort key.

getIcon(JTable, int) - Method in class smile.swing.table.MultiColumnSortTableHeaderCellRenderer

Overridden to return an icon suitable to a sorted column, or null if the column is unsorted.

getIconHeight() - Method in class smile.swing.AlphaIcon

Gets the height of the bounding rectangle of this AlphaIcon.

getIconWidth() - Method in class smile.swing.AlphaIcon

Gets the width of the bounding rectangle of this AlphaIcon.

getIndegree(int) - Method in class smile.graph.AdjacencyList

getIndegree(int) - Method in class smile.graph.AdjacencyMatrix

getIndegree(int) - Method in interface smile.graph.Graph

Returns the in-degree of the specified vertex.

getInitialStateProbabilities() - Method in class smile.sequence.HMM

Returns the initial state probabilities.

getInputSize() - Method in class smile.base.mlp.Layer

Returns the dimension of input vector (not including bias value).

getInstance() - Static method in interface smile.math.blas.BLAS

Creates an instance.

getInstance() - Static method in interface smile.math.blas.LAPACK

Creates an instance.

getInstance() - Static method in class smile.nlp.dictionary.EnglishPunctuations

Returns the singleton instance.

getInstance() - Static method in class smile.nlp.normalizer.SimpleNormalizer

Returns the singleton instance.

getInstance() - Static method in class smile.nlp.tokenizer.PennTreebankTokenizer

Returns the singleton instance.

getInstance() - Static method in class smile.nlp.tokenizer.SimpleParagraphSplitter

Returns the singleton instance.

getInstance() - Static method in class smile.nlp.tokenizer.SimpleSentenceSplitter

Returns the singleton instance.

getInstance() - Static method in class smile.stat.distribution.GaussianDistribution

Returns the standard normal distribution.

getInstance() - Static method in class smile.swing.FileChooser

Returns the shared file chooser instance.

getInstance() - Static method in class smile.swing.FontChooser

Returns the shared font chooser instance.

getInstance() - Static method in class smile.swing.table.DoubleCellEditor

Returns the default instance.

getInt(int) - Method in interface smile.data.Tuple

Returns the value at position i as a primitive int.

getInt(int) - Method in interface smile.data.vector.BaseVector

Returns the integer value at position i.

getInt(int) - Method in interface smile.data.vector.BooleanVector

getInt(int) - Method in interface smile.data.vector.ByteVector

getInt(int) - Method in interface smile.data.vector.CharVector

getInt(int) - Method in interface smile.data.vector.DoubleVector

getInt(int) - Method in interface smile.data.vector.FloatVector

getInt(int) - Method in interface smile.data.vector.LongVector

getInt(int) - Method in interface smile.data.vector.ShortVector

getInt(int) - Method in interface smile.data.vector.StringVector

getInt(int) - Method in interface smile.data.vector.Vector

getInt(int...) - Method in class smile.deep.tensor.Tensor

Returns the int value of element at given index.

getInt(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) as a primitive int.

getInt(int, String) - Method in interface smile.data.DataFrame

Returns the field value as a primitive int.

getInt(long...) - Method in class smile.deep.tensor.Tensor

Returns the int value of element at given index.

getInt(String) - Method in interface smile.data.Tuple

Returns the field value as a primitive int.

getKey() - Method in class smile.nlp.Trie.Node

Returns the key.

getLabel() - Method in class smile.plot.swing.Axis

Returns the label of the axis.

getLearningRate() - Method in class smile.base.mlp.MultilayerPerceptron

Returns the learning rate.

getLearningRate() - Method in class smile.classification.LogisticRegression

Returns the learning rate of stochastic gradient descent.

getLearningRate() - Method in class smile.classification.Maxent

Returns the learning rate of stochastic gradient descent.

getLearningRate() - Method in class smile.classification.SparseLogisticRegression

Returns the learning rate of stochastic gradient descent.

getLocalSearchSteps() - Method in class smile.gap.GeneticAlgorithm

Gets the number of iterations of local search in Lamarckian algorithm.

getLong(int) - Method in interface smile.data.Tuple

Returns the value at position i as a primitive long.

getLong(int) - Method in interface smile.data.vector.BaseVector

Returns the long value at position i.

getLong(int) - Method in interface smile.data.vector.BooleanVector

getLong(int) - Method in interface smile.data.vector.ByteVector

getLong(int) - Method in interface smile.data.vector.CharVector

getLong(int) - Method in interface smile.data.vector.DoubleVector

getLong(int) - Method in interface smile.data.vector.FloatVector

getLong(int) - Method in interface smile.data.vector.IntVector

getLong(int) - Method in interface smile.data.vector.ShortVector

getLong(int) - Method in interface smile.data.vector.StringVector

getLong(int) - Method in interface smile.data.vector.Vector

getLong(int...) - Method in class smile.deep.tensor.Tensor

Returns the long value of element at given index.

getLong(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) as a primitive long.

getLong(int, String) - Method in interface smile.data.DataFrame

Returns the field value as a primitive long.

getLong(long...) - Method in class smile.deep.tensor.Tensor

Returns the long value of element at given index.

getLong(String) - Method in interface smile.data.Tuple

Returns the field value as a primitive long.

getLowerBound() - Method in class smile.plot.swing.BarPlot

getLowerBound() - Method in class smile.plot.swing.BoxPlot

getLowerBound() - Method in class smile.plot.swing.Contour

getLowerBound() - Method in class smile.plot.swing.Dendrogram

getLowerBound() - Method in class smile.plot.swing.Graphics

Returns the lower bounds of coordinate space.

getLowerBound() - Method in class smile.plot.swing.Grid

getLowerBound() - Method in class smile.plot.swing.Heatmap

getLowerBound() - Method in class smile.plot.swing.Hexmap

getLowerBound() - Method in class smile.plot.swing.Histogram3D

getLowerBound() - Method in class smile.plot.swing.LinePlot

getLowerBound() - Method in class smile.plot.swing.Plot

Returns the lower bound of data.

getLowerBound() - Method in class smile.plot.swing.QQPlot

getLowerBound() - Method in class smile.plot.swing.ScatterPlot

getLowerBound() - Method in class smile.plot.swing.ScreePlot

getLowerBound() - Method in class smile.plot.swing.SparseMatrixPlot

getLowerBound() - Method in class smile.plot.swing.StaircasePlot

getLowerBound() - Method in class smile.plot.swing.Surface

getLowerBound() - Method in class smile.plot.swing.TextPlot

getLowerBound() - Method in class smile.plot.swing.Wireframe

getLowerBounds() - Method in class smile.plot.swing.Base

Returns the lower bounds.

getLowerBounds() - Method in class smile.plot.swing.Canvas

Returns the lower bounds.

getMargin() - Method in class smile.plot.swing.Canvas

Returns the size of margin, which is not used as plot area.

getMessage(String) - Method in class smile.swing.FontChooser

getMnemonic() - Method in class smile.swing.table.ButtonCellRenderer

getMomentum() - Method in class smile.base.mlp.MultilayerPerceptron

Returns the momentum factor.

getNumberFormat() - Method in class smile.swing.table.NumberCellRenderer

Returns the number format used for rendering.

getNumVertices() - Method in class smile.graph.AdjacencyList

getNumVertices() - Method in class smile.graph.AdjacencyMatrix

getNumVertices() - Method in interface smile.graph.Graph

Returns the number of vertices.

getObjectClass() - Method in class smile.data.type.ObjectType

Returns the class of objects.

getOutdegree(int) - Method in class smile.graph.AdjacencyList

getOutdegree(int) - Method in class smile.graph.AdjacencyMatrix

getOutdegree(int) - Method in interface smile.graph.Graph

Returns the out-degree of the specified vertex.

getOutputSize() - Method in class smile.base.mlp.Layer

Returns the dimension of output vector.

getPage() - Method in class smile.swing.table.PageTableModel

Returns the current page.

getPageCount() - Method in class smile.swing.table.PageTableModel

Returns the number of pages.

getPageSize() - Method in class smile.swing.table.PageTableModel

Returns the page size.

getPaint() - Method in class smile.plot.swing.Graphics

Get the current paint object.

getPathFromRoot() - Method in class smile.taxonomy.Concept

Returns the path from root to this node.

getPathToRoot() - Method in class smile.taxonomy.Concept

Returns the path from this node to the root.

getPrecisionDigits() - Method in class smile.plot.swing.Base

Returns the precision unit digits of axes.

getPrecisionUnit() - Method in class smile.plot.swing.Base

Returns the precision units of axes.

getPrinter() - Static method in class smile.swing.Printer

Returns the printer controller object.

getProbeSequence(double[], double, int) - Method in class smile.neighbor.lsh.PosterioriModel

Generate query-directed probes.

getProjection() - Method in class smile.classification.FLD

Returns the projection matrix W.

getProjection() - Method in class smile.plot.swing.Graphics

Returns the projection object.

getProjection(double) - Method in class smile.feature.extraction.PCA

Returns the projection with top principal components that contain (more than) the given percentage of variance.

getProjection(int) - Method in class smile.feature.extraction.PCA

Returns the projection with given number of principal components.

getPropertyChangeListeners() - Method in class smile.plot.swing.Canvas

Returns an array of all the listeners that were added to the PropertyChangeSupport object with addPropertyChangeListener().

getReadableImageFilter() - Static method in class smile.swing.FileChooser.SimpleFileFilter

Returns the filter for readable images.

getRealRow(int) - Method in class smile.swing.table.PageTableModel

Returns the row number of data given the row number of current page.

getRealRowCount() - Method in class smile.swing.table.PageTableModel

The sub class should implement this method to return the real number of rows in the model.

getrf(Layout, int, int, double[], int, int[]) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.

getrf(Layout, int, int, double[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

getrf(Layout, int, int, float[], int, int[]) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.

getrf(Layout, int, int, float[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

getrf(Layout, int, int, DoubleBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.

getrf(Layout, int, int, DoubleBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

getrf(Layout, int, int, FloatBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.

getrf(Layout, int, int, FloatBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

getrf(Layout, int, int, DoublePointer, int, IntPointer) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.

getrf(Layout, int, int, DoublePointer, int, IntPointer) - Method in class smile.math.blas.openblas.OpenBLAS

getrf2(Layout, int, int, double[], int, int[]) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.

getrf2(Layout, int, int, double[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

getrf2(Layout, int, int, float[], int, int[]) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.

getrf2(Layout, int, int, float[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

getrf2(Layout, int, int, DoubleBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.

getrf2(Layout, int, int, DoubleBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

getrf2(Layout, int, int, FloatBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK

Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.

getrf2(Layout, int, int, FloatBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

getRoot() - Method in class smile.taxonomy.Taxonomy

Returns the root node of taxonomy tree.

getRowCount() - Method in class smile.swing.table.PageTableModel

getRowCount() - Method in class smile.swing.Table.RowHeader

Delegate method to main table

getRowHeader() - Method in class smile.swing.Table

Returns a row header for this table.

getRowHeight(int) - Method in class smile.swing.Table.RowHeader

getrs(Layout, Transpose, int, int, double[], int, int[], double[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

getrs(Layout, Transpose, int, int, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

getrs(Layout, Transpose, int, int, float[], int, int[], float[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

getrs(Layout, Transpose, int, int, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

getrs(Layout, Transpose, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

getrs(Layout, Transpose, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

getrs(Layout, Transpose, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

getrs(Layout, Transpose, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

getrs(Layout, Transpose, int, int, DoublePointer, int, IntPointer, DoublePointer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

getrs(Layout, Transpose, int, int, DoublePointer, int, IntPointer, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

getScale(int) - Method in interface smile.data.Tuple

Returns the value at position i of NominalScale or OrdinalScale.

getScale(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) of NominalScale or OrdinalScale.

getScale(int, String) - Method in interface smile.data.DataFrame

Returns the field value of NominalScale or OrdinalScale.

getScale(String) - Method in interface smile.data.Tuple

Returns the field value of NominalScale or OrdinalScale.

getScrollableTracksViewportWidth() - Method in class smile.swing.Table

getSelectedFont() - Method in class smile.swing.FontChooser

Get the selected font.

getSelectedFontFamily() - Method in class smile.swing.FontChooser

Get the family name of the selected font.

getSelectedFontSize() - Method in class smile.swing.FontChooser

Get the size of the selected font.

getSelectedFontStyle() - Method in class smile.swing.FontChooser

Get the style of the selected font.

getShapes() - Method in class smile.plot.swing.Canvas

Returns the list of shapes in the canvas.

getShort(int) - Method in interface smile.data.Tuple

Returns the value at position i as a primitive short.

getShort(int) - Method in interface smile.data.vector.BaseVector

Returns the short value at position i.

getShort(int) - Method in interface smile.data.vector.BooleanVector

getShort(int) - Method in interface smile.data.vector.ByteVector

getShort(int) - Method in interface smile.data.vector.CharVector

getShort(int) - Method in interface smile.data.vector.DoubleVector

getShort(int) - Method in interface smile.data.vector.FloatVector

getShort(int) - Method in interface smile.data.vector.IntVector

getShort(int) - Method in interface smile.data.vector.LongVector

getShort(int) - Method in interface smile.data.vector.StringVector

getShort(int) - Method in interface smile.data.vector.Vector

getShort(int...) - Method in class smile.deep.tensor.Tensor

Returns the short value of element at given index.

getShort(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) as a primitive short.

getShort(int, String) - Method in interface smile.data.DataFrame

Returns the field value as a primitive short.

getShort(long...) - Method in class smile.deep.tensor.Tensor

Returns the short value of element at given index.

getShort(String) - Method in interface smile.data.Tuple

Returns the field value as a primitive short.

getSortKey(JTable, int) - Method in class smile.swing.table.DefaultTableHeaderCellRenderer

Returns the current sort key, or null if the column is unsorted.

getStateTransitionProbabilities() - Method in class smile.sequence.HMM

Returns the state transition probabilities.

getString(int) - Method in interface smile.data.Tuple

Returns the value at position i as a String object.

getString(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) as a String object.

getString(int, String) - Method in interface smile.data.DataFrame

Returns the field value as a String object.

getString(String) - Method in interface smile.data.Tuple

Returns the field value as a String object.

getStroke() - Method in class smile.plot.swing.Graphics

Get the current stroke.

getStruct(int) - Method in interface smile.data.Tuple

Returns the value at position i of struct type.

getStruct(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) of struct type.

getStruct(int, String) - Method in interface smile.data.DataFrame

Returns the field value of struct type.

getStruct(String) - Method in interface smile.data.Tuple

Returns the field value of struct type.

getSymbolEmissionProbabilities() - Method in class smile.sequence.HMM

Returns the symbol emission probabilities.

getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.ButtonCellRenderer

getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.ColorCellEditor

getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.DateCellEditor

getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.DoubleArrayCellEditor

getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.DoubleCellEditor

getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.FontCellEditor

getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.IntegerArrayCellEditor

getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.IntegerCellEditor

getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class smile.swing.table.ButtonCellRenderer

getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class smile.swing.table.ColorCellRenderer

getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class smile.swing.table.DefaultTableHeaderCellRenderer

Returns the default table header cell renderer.

getTestData(String...) - Static method in interface smile.util.Paths

Get the file path of a test sample dataset.

getTestDataLines(String...) - Static method in interface smile.util.Paths

Returns the reader of a test data.

getTestDataReader(String...) - Static method in interface smile.util.Paths

Returns the reader of a test data.

getTime(int) - Method in interface smile.data.Tuple

Returns the value at position i of date type as java.time.LocalTime.

getTime(int, int) - Method in interface smile.data.DataFrame

Returns the value at position (i, j) of date type as java.time.LocalTime.

getTime(int, String) - Method in interface smile.data.DataFrame

Returns the field value of date type as java.time.LocalTime.

getTime(String) - Method in interface smile.data.Tuple

Returns the field value of date type as java.time.LocalTime.

getTitle() - Method in class smile.plot.swing.Canvas

Returns the main title of canvas.

getTitleColor() - Method in class smile.plot.swing.Canvas

Returns the color for title.

getTitleFont() - Method in class smile.plot.swing.Canvas

Returns the font for title.

getToolbar() - Method in class smile.plot.swing.PlotPanel

Returns a tool bar to control the plot.

getToolbar() - Method in class smile.swing.table.PageTableModel

Returns a tool bar to control the plot.

getUpperBound() - Method in class smile.plot.swing.BarPlot

getUpperBound() - Method in class smile.plot.swing.BoxPlot

getUpperBound() - Method in class smile.plot.swing.Contour

getUpperBound() - Method in class smile.plot.swing.Dendrogram

getUpperBound() - Method in class smile.plot.swing.Graphics

Returns the upper bounds of coordinate space.

getUpperBound() - Method in class smile.plot.swing.Grid

getUpperBound() - Method in class smile.plot.swing.Heatmap

getUpperBound() - Method in class smile.plot.swing.Hexmap

getUpperBound() - Method in class smile.plot.swing.Histogram3D

getUpperBound() - Method in class smile.plot.swing.LinePlot

getUpperBound() - Method in class smile.plot.swing.Plot

Returns the upper bound of data.

getUpperBound() - Method in class smile.plot.swing.QQPlot

getUpperBound() - Method in class smile.plot.swing.ScatterPlot

getUpperBound() - Method in class smile.plot.swing.ScreePlot

getUpperBound() - Method in class smile.plot.swing.SparseMatrixPlot

getUpperBound() - Method in class smile.plot.swing.StaircasePlot

getUpperBound() - Method in class smile.plot.swing.Surface

getUpperBound() - Method in class smile.plot.swing.TextPlot

getUpperBound() - Method in class smile.plot.swing.Wireframe

getUpperBounds() - Method in class smile.plot.swing.Base

Returns the upper bounds.

getUpperBounds() - Method in class smile.plot.swing.Canvas

Returns the upper bounds.

getValue() - Method in class smile.nlp.Trie.Node

Returns the value.

getValue(String) - Static method in enum class smile.nlp.pos.PennTreebankPOS

Returns an enum value from a string.

getValueAt(int, int) - Method in class smile.swing.table.PageTableModel

getValueAt(int, int) - Method in class smile.swing.Table.RowHeader

This table does not use any data from the main TableModel, so just return a value based on the row parameter.

getValueAtRealRow(int, int) - Method in class smile.swing.table.PageTableModel

Returns the value for the cell at real row index.

getWeight(int, int) - Method in class smile.graph.AdjacencyList

getWeight(int, int) - Method in class smile.graph.AdjacencyMatrix

getWeight(int, int) - Method in interface smile.graph.Graph

Returns the weight assigned to a given edge.

getWeightDecay() - Method in class smile.base.mlp.MultilayerPerceptron

Returns the weight decay factor.

getWritableImageFIlter() - Static method in class smile.swing.FileChooser.SimpleFileFilter

Returns the filter for writable images.

ggglm(Layout, int, int, int, double[], int, double[], int, double[], double[], double[]) - Method in interface smile.math.blas.LAPACK

Solves a general Gauss-Markov linear model (GLM) problem.

ggglm(Layout, int, int, int, double[], int, double[], int, double[], double[], double[]) - Method in class smile.math.blas.openblas.OpenBLAS

ggglm(Layout, int, int, int, float[], int, float[], int, float[], float[], float[]) - Method in interface smile.math.blas.LAPACK

Solves a general Gauss-Markov linear model (GLM) problem.

ggglm(Layout, int, int, int, float[], int, float[], int, float[], float[], float[]) - Method in class smile.math.blas.openblas.OpenBLAS

ggglm(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, DoubleBuffer) - Method in interface smile.math.blas.LAPACK

Solves a general Gauss-Markov linear model (GLM) problem.

ggglm(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

ggglm(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, FloatBuffer, FloatBuffer, FloatBuffer) - Method in interface smile.math.blas.LAPACK

Solves a general Gauss-Markov linear model (GLM) problem.

ggglm(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, FloatBuffer, FloatBuffer, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gglse(Layout, int, int, int, double[], int, double[], int, double[], double[], double[]) - Method in interface smile.math.blas.LAPACK

Solves a linear equality-constrained least squares (LSE) problem.

gglse(Layout, int, int, int, double[], int, double[], int, double[], double[], double[]) - Method in class smile.math.blas.openblas.OpenBLAS

gglse(Layout, int, int, int, float[], int, float[], int, float[], float[], float[]) - Method in interface smile.math.blas.LAPACK

Solves a linear equality-constrained least squares (LSE) problem.

gglse(Layout, int, int, int, float[], int, float[], int, float[], float[], float[]) - Method in class smile.math.blas.openblas.OpenBLAS

gglse(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, DoubleBuffer) - Method in interface smile.math.blas.LAPACK

Solves a linear equality-constrained least squares (LSE) problem.

gglse(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

gglse(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, FloatBuffer, FloatBuffer, FloatBuffer) - Method in interface smile.math.blas.LAPACK

Solves a linear equality-constrained least squares (LSE) problem.

gglse(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, FloatBuffer, FloatBuffer, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

GHA - Class in smile.feature.extraction

Generalized Hebbian Algorithm.

GHA(double[][], TimeFunction, String...) - Constructor for class smile.feature.extraction.GHA

Constructor.

GHA(int, int, TimeFunction, String...) - Constructor for class smile.feature.extraction.GHA

Constructor.

GINI - Enum constant in enum class smile.base.cart.SplitRule

Used by the CART algorithm, Gini impurity is a measure of how often a randomly chosen element from the set would be incorrectly labeled if it were randomly labeled according to the distribution of labels in the subset.

GLM - Class in smile.glm

Generalized linear models.

GLM(Formula, String[], Model, double[], double, double, double, double[], double[], double[][]) - Constructor for class smile.glm.GLM

Constructor.

GloVe - Class in smile.nlp.embedding

Global Vectors for Word Representation.

GloVe() - Constructor for class smile.nlp.embedding.GloVe

GLU - Class in smile.deep.activation

Gated Linear Unit activation function.

GLU() - Constructor for class smile.deep.activation.GLU

Constructor.

GMeans - Class in smile.clustering

G-Means clustering algorithm, an extended K-Means which tries to automatically determine the number of clusters by normality test.

GMeans(double, double[][], int[]) - Constructor for class smile.clustering.GMeans

Constructor.

GOLD - Static variable in interface smile.plot.swing.Palette

GoodTuring - Class in smile.stat

Good–Turing frequency estimation.

GOOGLE - Enum constant in enum class smile.nlp.dictionary.EnglishStopWords

The stop words list used by Google.

gradient() - Method in class smile.base.mlp.Layer

Returns the output gradient vector.

gradientLength(double) - Method in class smile.plot.vega.Legend

Sets the length in pixels of the primary axis of a color gradient.

gradientOpacity(double) - Method in class smile.plot.vega.Legend

Sets the opacity of the color gradient.

gradientStrokeColor(String) - Method in class smile.plot.vega.Legend

Sets the color of the gradient stroke.

gradientStrokeWidth(double) - Method in class smile.plot.vega.Legend

Sets the width of the gradient stroke.

gradientThickness(double) - Method in class smile.plot.vega.Legend

Sets the thickness in pixels of the color gradient.

GradientTreeBoost - Class in smile.classification

Gradient boosting for classification.

GradientTreeBoost - Class in smile.regression

Gradient boosting for regression.

GradientTreeBoost(Formula, RegressionTree[][], double, double[]) - Constructor for class smile.classification.GradientTreeBoost

Constructor of multi-class.

GradientTreeBoost(Formula, RegressionTree[][], double, double[], IntSet) - Constructor for class smile.classification.GradientTreeBoost

Constructor of multi-class.

GradientTreeBoost(Formula, RegressionTree[], double, double, double[]) - Constructor for class smile.classification.GradientTreeBoost

Constructor of binary class.

GradientTreeBoost(Formula, RegressionTree[], double, double, double[]) - Constructor for class smile.regression.GradientTreeBoost

Constructor.

GradientTreeBoost(Formula, RegressionTree[], double, double, double[], IntSet) - Constructor for class smile.classification.GradientTreeBoost

Constructor of binary class.

graph - Variable in class smile.manifold.IsoMap

The nearest neighbor graph.

graph - Variable in class smile.manifold.LaplacianEigenmap

Nearest neighbor graph.

graph - Variable in class smile.manifold.LLE

Nearest neighbor graph.

graph - Variable in class smile.manifold.UMAP

The nearest neighbor graph.

Graph - Interface in smile.graph

A graph is an abstract representation of a set of objects where some pairs of the objects are connected by links.

Graph.Edge - Class in smile.graph

Graph edge.

Graphics - Class in smile.plot.swing

Graphics provides methods to draw graphical primitives in logical/mathematical coordinates.

Graphics(Projection) - Constructor for class smile.plot.swing.Graphics

Constructor.

GRASS_GREEN - Static variable in interface smile.plot.swing.Palette

GREEN - Static variable in interface smile.plot.swing.Palette

grid() - Method in class smile.hpo.Hyperparameters

Generates a stream of hyperparameters for grid search.

grid(boolean) - Method in class smile.plot.vega.Axis

Sets if gridlines should be included as part of the axis.

Grid - Class in smile.plot.swing

A 2D grid plot.

Grid(double[][][], Color) - Constructor for class smile.plot.swing.Grid

Constructor.

gridAlign(String) - Method in class smile.plot.vega.Legend

Sets the alignment to apply to symbol legends rows and columns.

gridCap(String) - Method in class smile.plot.vega.Axis

Sets the stroke cap for gridlines' ending style.

gridColor(String) - Method in class smile.plot.vega.Axis

Sets the color of gridlines.

gridDash(double, double) - Method in class smile.plot.vega.Axis

Sets the alternating [stroke, space] lengths for dashed gridlines.

gridOpacity(double) - Method in class smile.plot.vega.Axis

Sets the stroke opacity of grid.

gridWidth(double) - Method in class smile.plot.vega.Axis

Sets the grid width.

groupby(String...) - Method in class smile.plot.vega.ImputeTransform

Sets the data fields by which to group the values.

groupby(String...) - Method in class smile.plot.vega.LoessTransform

Sets the data fields to group by.

groupby(String...) - Method in class smile.plot.vega.PivotTransform

Sets the data fields to group by.

groupby(String...) - Method in class smile.plot.vega.QuantileTransform

Sets the data fields to group by.

groupby(String...) - Method in class smile.plot.vega.RegressionTransform

Sets the data fields to group by.

groupby(String...) - Method in class smile.plot.vega.WindowTransform

Sets the data fields for partitioning the data objects into separate windows.

GroupNormLayer - Class in smile.deep.layer

Group normalization.

GroupNormLayer(int, int) - Constructor for class smile.deep.layer.GroupNormLayer

Constructor.

GroupNormLayer(int, int, double, boolean) - Constructor for class smile.deep.layer.GroupNormLayer

Constructor.

groups() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns the value of the groups record component.

GrowingNeuralGas - Class in smile.vq

Growing Neural Gas.

GrowingNeuralGas(int) - Constructor for class smile.vq.GrowingNeuralGas

Constructor.

GrowingNeuralGas(int, double, double, int, int, double, double) - Constructor for class smile.vq.GrowingNeuralGas

Constructor.

gt(double) - Method in class smile.deep.tensor.Tensor

Computes element-wise greater-than comparison.

gt(int) - Method in class smile.deep.tensor.Tensor

Computes element-wise greater-than comparison.

gt(Tensor) - Method in class smile.deep.tensor.Tensor

Computes element-wise greater-than comparison.

H

H - Variable in class smile.neighbor.LSH

The size of hash table.

H - Variable in class smile.neighbor.lsh.NeighborHashValueModel

The hash values of query object.

HaarWavelet - Class in smile.wavelet

Haar wavelet.

HaarWavelet() - Constructor for class smile.wavelet.HaarWavelet

Constructor.

HadoopInput - Interface in smile.io

Static methods that return the InputStream/Reader of a HDFS/S3.

HammingDistance - Class in smile.math.distance

In information theory, the Hamming distance between two strings of equal length is the number of positions for which the corresponding symbols are different.

HammingDistance() - Constructor for class smile.math.distance.HammingDistance

Constructor.

hardShrink(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with hard shrink activation function.

HardShrink - Class in smile.deep.activation

Hard Shrink activation function.

HardShrink() - Constructor for class smile.deep.activation.HardShrink

Constructor.

HardShrink(double) - Constructor for class smile.deep.activation.HardShrink

Constructor.

harwell(Path) - Static method in class smile.math.matrix.fp32.SparseMatrix

Reads a sparse matrix from a Harwell-Boeing Exchange Format file.

harwell(Path) - Static method in class smile.math.matrix.SparseMatrix

Reads a sparse matrix from a Harwell-Boeing Exchange Format file.

hasEdge(int, int) - Method in class smile.graph.AdjacencyList

hasEdge(int, int) - Method in class smile.graph.AdjacencyMatrix

hasEdge(int, int) - Method in interface smile.graph.Graph

Returns true if and only if this graph contains an edge going from the source vertex to the target vertex.

hash - Variable in class smile.neighbor.LSH

Hash functions.

hash(double[]) - Method in class smile.neighbor.lsh.Hash

Apply hash functions on given vector x.

hash(Hash, PrZ[]) - Method in class smile.neighbor.lsh.Probe

Returns the bucket number of the probe.

hash(T) - Method in interface smile.hash.SimHash

Return the hash code.

Hash - Class in smile.neighbor.lsh

The hash function for Euclidean spaces.

Hash(int, int, double, int) - Constructor for class smile.neighbor.lsh.Hash

Constructor.

hash128(ByteBuffer, int, int, long, long[]) - Static method in class smile.hash.MurmurHash3

128-bit MurmurHash3 for x64.

hash32(byte[], int, int, int) - Static method in class smile.hash.MurmurHash3

32-bit MurmurHash3.

hash32(String, int) - Static method in class smile.hash.MurmurHash3

32-bit MurmurHash3.

hash32(ByteBuffer, int, int, int) - Static method in interface smile.hash.MurmurHash2

32-bit MurmurHash.

hash64(ByteBuffer, int, int, long) - Static method in interface smile.hash.MurmurHash2

64-bit MurmurHash.

hashCode() - Method in class smile.association.AssociationRule

hashCode() - Method in class smile.association.ItemSet

hashCode() - Method in record class smile.data.SampleInstance

Returns a hash code value for this object.

hashCode() - Method in record class smile.deep.SampleBatch

Returns a hash code value for this object.

hashCode() - Method in record class smile.llm.Transformer.Options

Returns a hash code value for this object.

hashCode() - Method in class smile.math.Complex

hashCode() - Method in class smile.nlp.Bigram

hashCode() - Method in class smile.nlp.NGram

hashCode() - Method in class smile.nlp.SimpleText

hashCode() - Method in record class smile.plot.vega.SortField

Returns a hash code value for this object.

hashCode() - Method in record class smile.plot.vega.WindowTransformField

Returns a hash code value for this object.

hashCode() - Method in record class smile.util.Bytes

Returns a hash code value for this object.

hashCode() - Method in record class smile.util.IntPair

Returns a hash code value for this object.

hashCode() - Method in record class smile.util.Tuple2

Returns a hash code value for this object.

hashCode() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns a hash code value for this object.

hashCode() - Method in record class smile.vision.layer.MBConvConfig

Returns a hash code value for this object.

HashEncoder - Class in smile.feature.extraction

Feature hashing, also known as the hashing trick, is a fast and space-efficient way of vectorizing features, i.e.

HashEncoder(Function<String, String[]>, int) - Constructor for class smile.feature.extraction.HashEncoder

Constructor.

HashEncoder(Function<String, String[]>, int, boolean) - Constructor for class smile.feature.extraction.HashEncoder

Constructor.

HashValueParzenModel - Class in smile.neighbor.lsh

Hash value Parzen model for multi-probe hash.

HashValueParzenModel(MultiProbeHash, MultiProbeSample[], double) - Constructor for class smile.neighbor.lsh.HashValueParzenModel

Constructor.

hasMissing(Tuple) - Static method in class smile.feature.imputation.SimpleImputer

Return true if the tuple x has missing values.

hasNull() - Method in interface smile.data.Tuple

Returns true if the tuple has null/missing values.

header(String) - Method in class smile.plot.vega.FacetField

Sets the header of facet.

Headless - Class in smile.plot.swing

Aids in creating swing components in a "headless" environment.

Headless(JComponent, int, int) - Constructor for class smile.plot.swing.Headless

heapify() - Method in class smile.sort.HeapSelect

In case of avoiding creating new objects frequently, one may check and update the peek object directly and call this method to sort the internal array in heap order.

HeapSelect<T> - Class in smile.sort

This class tracks the smallest values seen thus far in a stream of values.

HeapSelect(Class<?>, int) - Constructor for class smile.sort.HeapSelect

Constructor.

HeapSelect(T[]) - Constructor for class smile.sort.HeapSelect

Constructor.

HeapSort - Interface in smile.sort

Heapsort is a comparison-based sorting algorithm, and is part of the selection sort family.

heat(int) - Static method in interface smile.plot.swing.Palette

Generate heat color palette.

heat(int, float) - Static method in interface smile.plot.swing.Palette

Generate heat color palette.

Heatmap - Class in smile.plot.swing

A heat map is a graphical representation of data where the values taken by a variable in a two-dimensional map are represented as colors.

Heatmap(double[], double[], double[][], Color[]) - Constructor for class smile.plot.swing.Heatmap

Constructor.

Heatmap(String[], String[], double[][], Color[]) - Constructor for class smile.plot.swing.Heatmap

Constructor.

height() - Method in class smile.clustering.HierarchicalClustering

Returns a set of n-1 non-decreasing real values, which are the clustering height, i.e., the value of the criterion associated with the clustering method for the particular agglomeration.

height(double) - Method in class smile.plot.vega.Mark

Sets the height of the marks.

height(int) - Method in class smile.plot.vega.Layer

height(int) - Method in class smile.plot.vega.View

Sets the height of a plot with a continuous y-field, or the fixed height of a plot a discrete y-field or no y-field.

height(String) - Method in class smile.plot.vega.Layer

height(String) - Method in class smile.plot.vega.View

To enable responsive sizing on height.

heightStep(int) - Method in class smile.plot.vega.Layer

heightStep(int) - Method in class smile.plot.vega.View

For a discrete y-field, sets the height per discrete step..

HellingerKernel - Class in smile.math.kernel

The Hellinger kernel.

HellingerKernel() - Constructor for class smile.math.kernel.HellingerKernel

Constructor.

Hexmap - Class in smile.plot.swing

Hexmap is a variant of heat map by replacing rectangle cells with hexagon cells.

Hexmap(double[][], Color[], Hexmap.Tooltip) - Constructor for class smile.plot.swing.Hexmap

Constructor.

Hexmap.Tooltip - Interface in smile.plot.swing

The lambda interface to retrieve the tooltip of cell.

HHMM - Static variable in class smile.swing.table.DateCellEditor

HHMM - Static variable in class smile.swing.table.DateCellRenderer

HHMMSS - Static variable in class smile.swing.table.DateCellEditor

HHMMSS - Static variable in class smile.swing.table.DateCellRenderer

hi() - Method in class smile.math.kernel.BinarySparseGaussianKernel

hi() - Method in class smile.math.kernel.BinarySparseHyperbolicTangentKernel

hi() - Method in class smile.math.kernel.BinarySparseLaplacianKernel

hi() - Method in class smile.math.kernel.BinarySparseLinearKernel

hi() - Method in class smile.math.kernel.BinarySparseMaternKernel

hi() - Method in class smile.math.kernel.BinarySparsePolynomialKernel

hi() - Method in class smile.math.kernel.BinarySparseThinPlateSplineKernel

hi() - Method in class smile.math.kernel.GaussianKernel

hi() - Method in class smile.math.kernel.HellingerKernel

hi() - Method in class smile.math.kernel.HyperbolicTangentKernel

hi() - Method in class smile.math.kernel.LaplacianKernel

hi() - Method in class smile.math.kernel.LinearKernel

hi() - Method in class smile.math.kernel.MaternKernel

hi() - Method in interface smile.math.kernel.MercerKernel

Returns the upper bound of hyperparameters (in hyperparameter tuning).

hi() - Method in class smile.math.kernel.PearsonKernel

hi() - Method in class smile.math.kernel.PolynomialKernel

hi() - Method in class smile.math.kernel.ProductKernel

hi() - Method in class smile.math.kernel.SparseGaussianKernel

hi() - Method in class smile.math.kernel.SparseHyperbolicTangentKernel

hi() - Method in class smile.math.kernel.SparseLaplacianKernel

hi() - Method in class smile.math.kernel.SparseLinearKernel

hi() - Method in class smile.math.kernel.SparseMaternKernel

hi() - Method in class smile.math.kernel.SparsePolynomialKernel

hi() - Method in class smile.math.kernel.SparseThinPlateSplineKernel

hi() - Method in class smile.math.kernel.SumKernel

hi() - Method in class smile.math.kernel.ThinPlateSplineKernel

HiddenLayer - Class in smile.base.mlp

A hidden layer in the neural network.

HiddenLayer(int, int, double, ActivationFunction) - Constructor for class smile.base.mlp.HiddenLayer

Constructor.

HiddenLayerBuilder - Class in smile.base.mlp

The builder of hidden layers.

HiddenLayerBuilder(int, double, ActivationFunction) - Constructor for class smile.base.mlp.HiddenLayerBuilder

Constructor.

HierarchicalClustering - Class in smile.clustering

Agglomerative Hierarchical Clustering.

HierarchicalClustering(int[][], double[]) - Constructor for class smile.clustering.HierarchicalClustering

Constructor.

hingeEmbedding() - Static method in interface smile.deep.Loss

Hinge Embedding Loss Function.

Histogram - Class in smile.plot.swing

A histogram is a graphical display of tabulated frequencies, shown as bars.

Histogram - Interface in smile.math

Histogram utilities.

Histogram() - Constructor for class smile.plot.swing.Histogram

Histogram3D - Class in smile.plot.swing

A histogram is a graphical display of tabulated frequencies, shown as bars.

Histogram3D(double[][], int, int, boolean, Color[]) - Constructor for class smile.plot.swing.Histogram3D

Constructor.

HMM - Class in smile.sequence

First-order Hidden Markov Model.

HMM(double[], Matrix, Matrix) - Constructor for class smile.sequence.HMM

Constructor.

HMMLabeler<T> - Class in smile.sequence

First-order Hidden Markov Model sequence labeler.

HMMLabeler(HMM, ToIntFunction<T>) - Constructor for class smile.sequence.HMMLabeler

Constructor.

HMMPOSTagger - Class in smile.nlp.pos

Part-of-speech tagging with hidden Markov model.

HMMPOSTagger() - Constructor for class smile.nlp.pos.HMMPOSTagger

Constructor.

home - Static variable in interface smile.util.Paths

Smile home directory.

horizontal(VegaLite...) - Static method in class smile.plot.vega.Concat

Returns a horizontal concatenation of views.

HOUR - Enum constant in enum class smile.data.formula.DateFeature

The hours represented by an integer from 0 to 23.

hsv(float, float, float, float) - Static method in interface smile.plot.swing.Palette

Generate a color based on HSV model.

html() - Method in class smile.plot.vega.VegaLite

Returns the HTML of plot specification with Vega Embed.

html(String) - Method in class smile.plot.vega.VegaLite

Returns the HTML of plot specification with Vega Embed.

htmlEscape(String) - Static method in interface smile.util.Strings

Turn special characters into HTML character references.

htmlEscape(String, String) - Static method in interface smile.util.Strings

Turn special characters into HTML character references.

huber(double) - Static method in interface smile.base.cart.Loss

Huber loss function for M-regression, which attempts resistance to long-tailed error distributions and outliers while maintaining high efficiency for normally distributed errors.

Huber - Enum constant in enum class smile.base.cart.Loss.Type

Huber loss function for M-regression, which attempts resistance to long-tailed error distributions and outliers while maintaining high efficiency for normally distributed errors.

HyperbolicTangent - Class in smile.math.kernel

The hyperbolic tangent kernel.

HyperbolicTangent(double, double, double[], double[]) - Constructor for class smile.math.kernel.HyperbolicTangent

Constructor.

HyperbolicTangentKernel - Class in smile.math.kernel

The hyperbolic tangent kernel.

HyperbolicTangentKernel() - Constructor for class smile.math.kernel.HyperbolicTangentKernel

Constructor with scale 1.0 and offset 0.0.

HyperbolicTangentKernel(double, double) - Constructor for class smile.math.kernel.HyperbolicTangentKernel

Constructor.

HyperbolicTangentKernel(double, double, double[], double[]) - Constructor for class smile.math.kernel.HyperbolicTangentKernel

Constructor.

HyperGeometricDistribution - Class in smile.stat.distribution

The hypergeometric distribution is a discrete probability distribution that describes the number of successes in a sequence of n draws from a finite population without replacement, just as the binomial distribution describes the number of successes for draws with replacement.

HyperGeometricDistribution(int, int, int) - Constructor for class smile.stat.distribution.HyperGeometricDistribution

Constructor.

hyperparameters() - Method in class smile.math.kernel.BinarySparseGaussianKernel

hyperparameters() - Method in class smile.math.kernel.BinarySparseHyperbolicTangentKernel

hyperparameters() - Method in class smile.math.kernel.BinarySparseLaplacianKernel

hyperparameters() - Method in class smile.math.kernel.BinarySparseLinearKernel

hyperparameters() - Method in class smile.math.kernel.BinarySparseMaternKernel

hyperparameters() - Method in class smile.math.kernel.BinarySparsePolynomialKernel

hyperparameters() - Method in class smile.math.kernel.BinarySparseThinPlateSplineKernel

hyperparameters() - Method in class smile.math.kernel.GaussianKernel

hyperparameters() - Method in class smile.math.kernel.HellingerKernel

hyperparameters() - Method in class smile.math.kernel.HyperbolicTangentKernel

hyperparameters() - Method in class smile.math.kernel.LaplacianKernel

hyperparameters() - Method in class smile.math.kernel.LinearKernel

hyperparameters() - Method in class smile.math.kernel.MaternKernel

hyperparameters() - Method in interface smile.math.kernel.MercerKernel

Returns the hyperparameters of kernel.

hyperparameters() - Method in class smile.math.kernel.PearsonKernel

hyperparameters() - Method in class smile.math.kernel.PolynomialKernel

hyperparameters() - Method in class smile.math.kernel.ProductKernel

hyperparameters() - Method in class smile.math.kernel.SparseGaussianKernel

hyperparameters() - Method in class smile.math.kernel.SparseHyperbolicTangentKernel

hyperparameters() - Method in class smile.math.kernel.SparseLaplacianKernel

hyperparameters() - Method in class smile.math.kernel.SparseLinearKernel

hyperparameters() - Method in class smile.math.kernel.SparseMaternKernel

hyperparameters() - Method in class smile.math.kernel.SparsePolynomialKernel

hyperparameters() - Method in class smile.math.kernel.SparseThinPlateSplineKernel

hyperparameters() - Method in class smile.math.kernel.SumKernel

hyperparameters() - Method in class smile.math.kernel.ThinPlateSplineKernel

Hyperparameters - Class in smile.hpo

Hyperparameter configuration.

Hyperparameters() - Constructor for class smile.hpo.Hyperparameters

Constructor.

Hypothesis - Interface in smile.stat

Hypothesis test functions.

Hypothesis.chisq - Interface in smile.stat

Chi-square test.

Hypothesis.cor - Interface in smile.stat

Correlation test.

Hypothesis.F - Interface in smile.stat

F-test.

Hypothesis.KS - Interface in smile.stat

The Kolmogorov-Smirnov test (K-S test).

Hypothesis.t - Interface in smile.stat

t-test.

I

i - Variable in class smile.math.matrix.fp32.SparseMatrix.Entry

The row index.

i - Variable in class smile.math.matrix.SparseMatrix.Entry

The row index.

i - Variable in class smile.util.SparseArray.Entry

The index of entry.

iamax(double[]) - Method in interface smile.math.blas.BLAS

Searches a vector for the first occurrence of the the maximum absolute value.

iamax(float[]) - Method in interface smile.math.blas.BLAS

Searches a vector for the first occurrence of the the maximum absolute value.

iamax(int, double[], int) - Method in interface smile.math.blas.BLAS

Searches a vector for the first occurrence of the the maximum absolute value.

iamax(int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

iamax(int, float[], int) - Method in interface smile.math.blas.BLAS

Searches a vector for the first occurrence of the the maximum absolute value.

iamax(int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

ICA - Class in smile.ica

Independent Component Analysis (ICA) is a computational method for separating a multivariate signal into additive components.

id - Variable in class smile.nlp.Text

The id of document in the corpus.

id() - Method in class smile.data.type.ArrayType

id() - Method in class smile.data.type.BooleanType

id() - Method in class smile.data.type.ByteType

id() - Method in class smile.data.type.CharType

id() - Method in interface smile.data.type.DataType

Returns the type ID enum.

id() - Method in class smile.data.type.DateTimeType

id() - Method in class smile.data.type.DateType

id() - Method in class smile.data.type.DecimalType

id() - Method in class smile.data.type.DoubleType

id() - Method in class smile.data.type.FloatType

id() - Method in class smile.data.type.IntegerType

id() - Method in class smile.data.type.LongType

id() - Method in class smile.data.type.ObjectType

id() - Method in class smile.data.type.ShortType

id() - Method in class smile.data.type.StringType

id() - Method in class smile.data.type.StructType

id() - Method in class smile.data.type.TimeType

iframe() - Method in class smile.plot.vega.VegaLite

Returns the HTML wrapped in an iframe to render in notebooks.

iframe(String) - Method in class smile.plot.vega.VegaLite

Returns the HTML wrapped in an iframe to render in notebooks.

ignorePeers(boolean) - Method in class smile.plot.vega.WindowTransform

Sets if the sliding window frame should ignore peer values (data that are considered identical by the sort criteria).

im - Variable in class smile.math.Complex

The imaginary part.

ImageDataset - Class in smile.vision

Each of these directories should contain one subdirectory for each class in the dataset.

ImageDataset(int, String, Transform, ToIntFunction<String>) - Constructor for class smile.vision.ImageDataset

Constructor.

ImageNet - Interface in smile.vision

ImageNet class labels.

IMatrix - Class in smile.math.matrix.fp32

Matrix base class.

IMatrix - Class in smile.math.matrix

Matrix base class.

IMatrix() - Constructor for class smile.math.matrix.fp32.IMatrix

IMatrix() - Constructor for class smile.math.matrix.IMatrix

IMatrix.Preconditioner - Interface in smile.math.matrix.fp32

The preconditioner matrix.

IMatrix.Preconditioner - Interface in smile.math.matrix

The preconditioner matrix.

importance - Variable in class smile.base.cart.CART

Variable importance.

importance() - Method in class smile.base.cart.CART

Returns the variable importance.

importance() - Method in class smile.classification.AdaBoost

Returns the variable importance.

importance() - Method in class smile.classification.GradientTreeBoost

Returns the variable importance.

importance() - Method in class smile.classification.RandomForest

Returns the variable importance.

importance() - Method in class smile.regression.GradientTreeBoost

Returns the variable importance.

importance() - Method in class smile.regression.RandomForest

Returns the variable importance.

impurity() - Method in class smile.base.cart.RegressionNode

Returns the residual sum of squares.

impurity(LeafNode) - Method in class smile.base.cart.CART

Returns the impurity of node.

impurity(LeafNode) - Method in class smile.classification.DecisionTree

impurity(LeafNode) - Method in class smile.regression.RegressionTree

impurity(SplitRule) - Method in class smile.base.cart.DecisionNode

Returns the impurity of node.

impurity(SplitRule, int, int[]) - Static method in class smile.base.cart.DecisionNode

Returns the impurity of samples.

impute(double[][]) - Static method in class smile.feature.imputation.SimpleImputer

Impute the missing values with column averages.

impute(double[][], int, int) - Static method in interface smile.feature.imputation.SVDImputer

Impute missing values in the dataset.

impute(String, String) - Method in class smile.plot.vega.Transform

Adds an impute transform.

ImputeTransform - Class in smile.plot.vega

The impute transform groups data and determines missing values of the key field within each group.

in() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns the value of the in record component.

IN - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Preposition or subordinating conjunction.

increment() - Method in class smile.util.MutableInt

Increment by one.

increment(int) - Method in class smile.util.MutableInt

Increment.

index - Variable in class smile.base.cart.CART

An index of samples to their original locations in training dataset.

index - Variable in class smile.manifold.IsoMap

The original sample index.

index - Variable in class smile.manifold.LaplacianEigenmap

The original sample index.

index - Variable in class smile.manifold.LLE

The original sample index.

index - Variable in class smile.manifold.UMAP

The original sample index.

index - Variable in class smile.math.matrix.fp32.SparseMatrix.Entry

The index to the matrix storage.

index - Variable in class smile.math.matrix.SparseMatrix.Entry

The index to the matrix storage.

index - Variable in class smile.neighbor.Neighbor

The index of neighbor object in the dataset.

index - Variable in class smile.util.IntSet

Map of values to index.

index() - Method in class smile.deep.tensor.Device

Returns the device index or ordinal, which identifies the specific compute device when there is more than one of a certain type.

index(int, int) - Method in class smile.math.matrix.BigMatrix

Returns the linearized index of matrix element.

index(int, int) - Method in class smile.math.matrix.fp32.Matrix

Returns the linearized index of matrix element.

index(int, int) - Method in class smile.math.matrix.Matrix

Returns the linearized index of matrix element.

Index - Class in smile.deep.tensor

Indexing a tensor.

INDEX - Enum constant in enum class smile.math.blas.EigenRange

The IL-th through IU-th eigenvalues will be found.

IndexDataFrame - Class in smile.data

A data frame with a new index instead of the default [0, n) row index.

IndexDataFrame(DataFrame, int[]) - Constructor for class smile.data.IndexDataFrame

Constructor.

indexOf(int) - Method in class smile.util.IntSet

Maps the value to index.

indexOf(int[]) - Method in class smile.classification.ClassLabels

Maps the class labels to index.

indexOf(String) - Method in interface smile.data.DataFrame

Returns the index of a given column name.

indexOf(String) - Method in class smile.data.IndexDataFrame

indexOf(String) - Method in interface smile.data.Tuple

Returns the index of a given field name.

indexOf(String) - Method in class smile.data.type.StructType

Returns the index of a field.

infer(String) - Static method in interface smile.data.type.DataType

Infers the type of a string.

inferSchema(BufferedReader, int) - Method in class smile.io.JSON

Infer the schema from the top n rows.

inferSchema(Reader, int) - Method in class smile.io.CSV

Infer the schema from the top n rows.

info - Variable in class smile.math.matrix.BandMatrix.LU

If info = 0, the LU decomposition was successful.

info - Variable in class smile.math.matrix.BigMatrix.LU

If info = 0, the LU decomposition was successful.

info - Variable in class smile.math.matrix.fp32.BandMatrix.LU

If info = 0, the LU decomposition was successful.

info - Variable in class smile.math.matrix.fp32.Matrix.LU

If info = 0, the LU decomposition was successful.

info - Variable in class smile.math.matrix.fp32.SymmMatrix.BunchKaufman

If info = 0, the LU decomposition was successful.

info - Variable in class smile.math.matrix.Matrix.LU

If info = 0, the LU decomposition was successful.

info - Variable in class smile.math.matrix.SymmMatrix.BunchKaufman

If info = 0, the LU decomposition was successful.

InformationValue - Class in smile.feature.selection

Information Value (IV) measures the predictive strength of a feature for a binary dependent variable.

InformationValue(String, double, double[], double[]) - Constructor for class smile.feature.selection.InformationValue

Constructor.

init() - Method in class smile.llm.Transformer

Initializes the model weights.

initHashTable(int, int, int, double, int) - Method in class smile.neighbor.LSH

Initialize the hash tables.

initHashTable(int, int, int, double, int) - Method in class smile.neighbor.MPLSH

innerRadius(double) - Method in class smile.plot.vega.Mark

Sets the secondary (inner) radius in pixels for arc mark.

input(int) - Static method in class smile.base.mlp.Layer

Returns an input layer.

input(int, double) - Static method in class smile.base.mlp.Layer

Returns an input layer.

Input - Interface in smile.io

Static methods that return the InputStream/Reader of a file or URL.

inputChannels() - Method in record class smile.vision.layer.MBConvConfig

Returns the value of the inputChannels record component.

InputLayer - Class in smile.base.mlp

An input layer in the neural network.

InputLayer(int) - Constructor for class smile.base.mlp.InputLayer

Constructor.

InputLayer(int, double) - Constructor for class smile.base.mlp.InputLayer

Constructor.

insert(int) - Method in class smile.util.PriorityQueue

Insert a new item into queue.

instance - Static variable in class smile.validation.metric.Accuracy

Default instance.

instance - Static variable in class smile.validation.metric.AdjustedRandIndex

Default instance.

instance - Static variable in class smile.validation.metric.AUC

Default instance.

instance - Static variable in class smile.validation.metric.Error

Default instance.

instance - Static variable in class smile.validation.metric.Fallout

Default instance.

instance - Static variable in class smile.validation.metric.FDR

Default instance.

instance - Static variable in class smile.validation.metric.LogLoss

Default instance.

instance - Static variable in class smile.validation.metric.MAD

Default instance.

instance - Static variable in class smile.validation.metric.MatthewsCorrelation

Default instance.

instance - Static variable in class smile.validation.metric.MSE

Default instance.

instance - Static variable in class smile.validation.metric.MutualInformation

Default instance.

instance - Static variable in class smile.validation.metric.Precision

Default instance.

instance - Static variable in class smile.validation.metric.R2

Default instance.

instance - Static variable in class smile.validation.metric.RandIndex

Default instance.

instance - Static variable in class smile.validation.metric.Recall

Default instance.

instance - Static variable in class smile.validation.metric.RMSE

Default instance.

instance - Static variable in class smile.validation.metric.RSS

Default instance.

instance - Static variable in class smile.validation.metric.Sensitivity

Default instance.

instance - Static variable in class smile.validation.metric.Specificity

Default instance.

Int16 - Enum constant in enum class smile.deep.tensor.ScalarType

16-bit integer.

Int32 - Enum constant in enum class smile.deep.tensor.ScalarType

32-bit integer.

Int64 - Enum constant in enum class smile.deep.tensor.ScalarType

64-bit integer.

Int8 - Enum constant in enum class smile.deep.tensor.ScalarType

8-bit integer.

IntArray2D - Class in smile.util

2-dimensional array of integers.

IntArray2D(int[][]) - Constructor for class smile.util.IntArray2D

Constructor.

IntArray2D(int, int) - Constructor for class smile.util.IntArray2D

Constructor of all-zero matrix.

IntArray2D(int, int, int) - Constructor for class smile.util.IntArray2D

Constructor.

IntArray2D(int, int, int[]) - Constructor for class smile.util.IntArray2D

Constructor.

IntArrayList - Class in smile.util

A resizeable, array-backed list of integer primitives.

IntArrayList() - Constructor for class smile.util.IntArrayList

Constructs an empty list.

IntArrayList(int) - Constructor for class smile.util.IntArrayList

Constructs an empty list with the specified initial capacity.

IntArrayList(int[]) - Constructor for class smile.util.IntArrayList

Constructs a list containing the values of the specified array.

IntDoubleHashMap - Class in smile.util

HashMap<int, double> for primitive types.

IntDoubleHashMap() - Constructor for class smile.util.IntDoubleHashMap

Constructs an empty HashMap with the default initial capacity (16) and the default load factor (0.75).

IntDoubleHashMap(int, float) - Constructor for class smile.util.IntDoubleHashMap

Constructor.

Integer - Enum constant in enum class smile.data.type.DataType.ID

Integer type ID.

INTEGER - Static variable in class smile.swing.table.NumberCellRenderer

INTEGER - Static variable in interface smile.util.Regex

Integer regular expression pattern.

INTEGER_REGEX - Static variable in interface smile.util.Regex

Integer regular expression.

IntegerArrayCellEditor - Class in smile.swing.table

Implements a cell editor that uses a formatted text field to edit int[] values.

IntegerArrayCellEditor() - Constructor for class smile.swing.table.IntegerArrayCellEditor

Constructor.

IntegerArrayCellRenderer - Class in smile.swing.table

Integer array renderer in JTable.

IntegerArrayCellRenderer() - Constructor for class smile.swing.table.IntegerArrayCellRenderer

Constructor.

IntegerArrayType - Static variable in class smile.data.type.DataTypes

Integer Array data type.

IntegerCellEditor - Class in smile.swing.table

Implements a cell editor that uses a formatted text field to edit Integer values.

IntegerCellEditor() - Constructor for class smile.swing.table.IntegerCellEditor

Constructor.

IntegerCellEditor(int, int) - Constructor for class smile.swing.table.IntegerCellEditor

Constructor.

IntegerObjectType - Static variable in class smile.data.type.DataTypes

Integer Object data type.

IntegerType - Class in smile.data.type

Integer data type.

IntegerType - Static variable in class smile.data.type.DataTypes

Integer data type.

interact(String...) - Static method in interface smile.data.formula.Terms

Factor interaction of two or more factors.

intercept() - Method in class smile.base.svm.KernelMachine

Returns the intercept.

intercept() - Method in class smile.regression.LinearModel

Returns the intercept.

intercept() - Method in class smile.timeseries.AR

Returns the intercept.

intercept() - Method in class smile.timeseries.ARMA

Returns the intercept.

intercept(double[]) - Method in interface smile.base.cart.Loss

Returns the intercept of model.

InternalNode - Class in smile.base.cart

An internal node in CART.

InternalNode(int, double, double, Node, Node) - Constructor for class smile.base.cart.InternalNode

Constructor.

interpolate(double) - Method in class smile.interpolation.AbstractInterpolation

interpolate(double) - Method in interface smile.interpolation.Interpolation

Given a value x, return an interpolated value.

interpolate(double) - Method in class smile.interpolation.KrigingInterpolation1D

interpolate(double) - Method in class smile.interpolation.RBFInterpolation1D

interpolate(double) - Method in class smile.interpolation.ShepardInterpolation1D

interpolate(double...) - Method in class smile.interpolation.KrigingInterpolation

Interpolate the function at given point.

interpolate(double...) - Method in class smile.interpolation.RBFInterpolation

Interpolate the function at given point.

interpolate(double...) - Method in class smile.interpolation.ShepardInterpolation

Interpolate the function at given point.

interpolate(double[][]) - Static method in class smile.interpolation.LaplaceInterpolation

Laplace interpolation.

interpolate(double[][], double) - Static method in class smile.interpolation.LaplaceInterpolation

Laplace interpolation.

interpolate(double[][], double, int) - Static method in class smile.interpolation.LaplaceInterpolation

Laplace interpolation.

interpolate(double, double) - Method in class smile.interpolation.BicubicInterpolation

interpolate(double, double) - Method in class smile.interpolation.BilinearInterpolation

interpolate(double, double) - Method in class smile.interpolation.CubicSplineInterpolation2D

interpolate(double, double) - Method in interface smile.interpolation.Interpolation2D

Interpolate the data at a given 2-dimensional point.

interpolate(double, double) - Method in class smile.interpolation.KrigingInterpolation2D

interpolate(double, double) - Method in class smile.interpolation.RBFInterpolation2D

interpolate(double, double) - Method in class smile.interpolation.ShepardInterpolation2D

interpolate(String) - Method in class smile.plot.vega.Mark

Sets the line interpolation method to use for line and area marks.

Interpolation - Interface in smile.interpolation

In numerical analysis, interpolation is a method of constructing new data points within the range of a discrete set of known data points.

Interpolation2D - Interface in smile.interpolation

Interpolation of 2-dimensional data.

IntervalScale - Class in smile.data.measure

The interval scale allows for the degree of difference between items, but not the ratio between them.

IntervalScale(NumberFormat) - Constructor for class smile.data.measure.IntervalScale

Constructor.

IntFunction - Class in smile.data.formula

The generic term of applying an integer function.

IntFunction - Interface in smile.math

An interface representing a univariate int function.

IntFunction(String, Term, IntFunction) - Constructor for class smile.data.formula.IntFunction

Constructor.

IntHashSet - Class in smile.util

HashSet<int> for primitive types.

IntHashSet() - Constructor for class smile.util.IntHashSet

Constructs an empty HashSet with the default initial capacity (16) and the default load factor (0.75).

IntHashSet(int, float) - Constructor for class smile.util.IntHashSet

Constructor.

IntHeapSelect - Class in smile.sort

This class tracks the smallest values seen thus far in a stream of values.

IntHeapSelect(int) - Constructor for class smile.sort.IntHeapSelect

Constructor.

IntHeapSelect(int[]) - Constructor for class smile.sort.IntHeapSelect

Constructor.

IntPair - Record Class in smile.util

A tuple of 2 integer elements.

IntPair(int, int) - Constructor for record class smile.util.IntPair

Creates an instance of a IntPair record class.

IntSet - Class in smile.util

A set of integers.

IntSet(int[]) - Constructor for class smile.util.IntSet

Constructor.

intValue() - Method in class smile.deep.tensor.Tensor

Returns the int value when the tensor holds a single value.

intVector(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

intVector(int) - Method in class smile.data.IndexDataFrame

intVector(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

intVector(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

IntVector - Interface in smile.data.vector

An immutable integer vector.

inv(double) - Method in interface smile.math.Function

Computes the value of the inverse function at x.

inv(double) - Method in class smile.math.Scaler

invalid(String) - Method in class smile.plot.vega.Mark

Sets how Vega-Lite should handle marks for invalid values (null and NaN).

inverf(double) - Static method in class smile.math.special.Erf

The inverse error function.

inverfc(double) - Static method in class smile.math.special.Erf

The inverse complementary error function.

inverse() - Method in class smile.math.matrix.BandMatrix.Cholesky

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.BandMatrix.LU

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.BigMatrix.Cholesky

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.BigMatrix

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.BigMatrix.LU

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.fp32.BandMatrix.Cholesky

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.fp32.BandMatrix.LU

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.fp32.Matrix.Cholesky

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.fp32.Matrix

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.fp32.Matrix.LU

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.fp32.SymmMatrix.BunchKaufman

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.fp32.SymmMatrix.Cholesky

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.Matrix.Cholesky

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.Matrix

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.Matrix.LU

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.SymmMatrix.BunchKaufman

Returns the inverse of matrix.

inverse() - Method in class smile.math.matrix.SymmMatrix.Cholesky

Returns the inverse of matrix.

inverse(double[]) - Method in class smile.wavelet.Wavelet

Inverse discrete wavelet transform.

inverse(double, double) - Static method in interface smile.math.TimeFunction

Returns the inverse decay function.

inverse(double, double, double) - Static method in interface smile.math.TimeFunction

Returns the inverse decay function.

inverse(double, double, double, boolean) - Static method in interface smile.math.TimeFunction

Returns the inverse decay function.

inverseCDF() - Method in class smile.stat.distribution.GaussianDistribution

Generates a Gaussian random number with the inverse CDF method.

InverseMultiquadricRadialBasis - Class in smile.math.rbf

Inverse multiquadric RBF.

InverseMultiquadricRadialBasis() - Constructor for class smile.math.rbf.InverseMultiquadricRadialBasis

Constructor.

InverseMultiquadricRadialBasis(double) - Constructor for class smile.math.rbf.InverseMultiquadricRadialBasis

Constructor.

inverseRegularizedIncompleteBetaFunction(double, double, double) - Static method in class smile.math.special.Beta

Inverse of regularized incomplete beta function.

inverseRegularizedIncompleteGamma(double, double) - Static method in class smile.math.special.Gamma

The inverse of regularized incomplete gamma function.

inverseTransformSampling() - Method in interface smile.stat.distribution.Distribution

Use inverse transform sampling (also known as the inverse probability integral transform or inverse transformation method or Smirnov transform) to draw a sample from the given distribution.

invert(DataFrame) - Method in class smile.data.transform.InvertibleColumnTransform

invert(DataFrame) - Method in interface smile.data.transform.InvertibleTransform

Inverse transform a data frame.

invert(Tuple) - Method in class smile.data.transform.InvertibleColumnTransform

invert(Tuple) - Method in interface smile.data.transform.InvertibleTransform

Inverse transform a tuple.

InvertibleColumnTransform - Class in smile.data.transform

Invertible column-wise transformation.

InvertibleColumnTransform(String, Map<String, Function>, Map<String, Function>) - Constructor for class smile.data.transform.InvertibleColumnTransform

Constructor.

InvertibleTransform - Interface in smile.data.transform

Invertible data transformation.

invlink(double) - Method in interface smile.glm.model.Model

The inverse of link function (aka the mean function).

ipiv - Variable in class smile.math.matrix.BandMatrix.LU

The pivot vector.

ipiv - Variable in class smile.math.matrix.BigMatrix.LU

The pivot vector.

ipiv - Variable in class smile.math.matrix.fp32.BandMatrix.LU

The pivot vector.

ipiv - Variable in class smile.math.matrix.fp32.Matrix.LU

The pivot vector.

ipiv - Variable in class smile.math.matrix.fp32.SymmMatrix.BunchKaufman

The pivot vector.

ipiv - Variable in class smile.math.matrix.Matrix.LU

The pivot vector.

ipiv - Variable in class smile.math.matrix.SymmMatrix.BunchKaufman

The pivot vector.

IQAgent - Class in smile.sort

Incremental quantile estimation.

IQAgent() - Constructor for class smile.sort.IQAgent

Constructor.

IQAgent(int) - Constructor for class smile.sort.IQAgent

Constructor.

isAncestorOf(Concept) - Method in class smile.taxonomy.Concept

Returns true if this concept is an ancestor of the given concept.

isAvailable() - Static method in interface smile.deep.CUDA

Returns true if CUDA is available.

isBoolean() - Method in class smile.data.type.BooleanType

isBoolean() - Method in interface smile.data.type.DataType

Returns true if the type is boolean or Boolean.

isBoolean() - Method in class smile.data.type.ObjectType

isByte() - Method in class smile.data.type.ByteType

isByte() - Method in interface smile.data.type.DataType

Returns true if the type is byte or Byte.

isByte() - Method in class smile.data.type.ObjectType

isCellEditable(int, int) - Method in class smile.swing.Table.RowHeader

Don't edit data in the main TableModel by mistake

isChar() - Method in class smile.data.type.CharType

isChar() - Method in interface smile.data.type.DataType

Returns true if the type is char or Char.

isChar() - Method in class smile.data.type.ObjectType

isCPU() - Method in class smile.deep.tensor.Device

Returns true if the device is CPU.

isCUDA() - Method in class smile.deep.tensor.Device

Returns true if the device is CUDA.

isDouble() - Method in interface smile.data.type.DataType

Returns true if the type is double or Double.

isDouble() - Method in class smile.data.type.DoubleType

isDouble() - Method in class smile.data.type.ObjectType

isDouble(DataType) - Static method in interface smile.data.type.DataType

Returns true if the given type is of double, either primitive or boxed.

isEmpty() - Method in interface smile.data.DataFrame

Returns true if the data frame is empty.

isEmpty() - Method in interface smile.data.Dataset

Returns true if the dataset is empty.

isEmpty() - Method in class smile.plot.swing.Isoline

Returns true if the isoline doesn't have any points.

isEmpty() - Method in class smile.util.DoubleArrayList

Returns true if this list contains no values.

isEmpty() - Method in class smile.util.IntArrayList

Returns true if this list contains no values.

isEmpty() - Method in class smile.util.PriorityQueue

Returns true if the queue is empty.

isEmpty() - Method in class smile.util.SparseArray

Returns true if the array is empty.

isExpandable() - Method in class smile.neighbor.lsh.Probe

Returns true if the probe is expandable.

isExtendable() - Method in class smile.neighbor.lsh.Probe

Returns true if the probe is extendable.

isFloat() - Method in interface smile.data.type.DataType

Returns true if the type is float or Float.

isFloat() - Method in class smile.data.type.FloatType

isFloat() - Method in class smile.data.type.ObjectType

isFloat(DataType) - Static method in interface smile.data.type.DataType

Returns true if the given type is of float, either primitive or boxed.

isFloating() - Method in interface smile.data.type.DataType

Returns true if the type is float or double.

isFrameVisible() - Method in class smile.plot.swing.Axis

Returns the visibility of the frame grid lines and their labels.

isGridVisible() - Method in class smile.plot.swing.Axis

Returns the visibility of the grid lines and their labels.

isInplace() - Method in class smile.deep.activation.ActivationFunction

Returns true if the operation executes in-place.

isInt() - Method in interface smile.data.type.DataType

Returns true if the type is int or Integer.

isInt() - Method in class smile.data.type.IntegerType

isInt() - Method in class smile.data.type.ObjectType

isInt(double) - Static method in class smile.math.MathEx

Returns true if x is an integer.

isInt(float) - Static method in class smile.math.MathEx

Returns true if x is an integer.

isInt(DataType) - Static method in interface smile.data.type.DataType

Returns true if the given type is of int, short, byte, char, either primitive or boxed.

isIntegral() - Method in interface smile.data.type.DataType

Returns true if the type is int, long, short or byte.

isLeaf() - Method in class smile.taxonomy.Concept

Check if a node is a leaf in the taxonomy tree.

isLegendVisible() - Method in class smile.plot.swing.Canvas

Returns true if legends are visible.

isLong() - Method in interface smile.data.type.DataType

Returns true if the type is long or Long.

isLong() - Method in class smile.data.type.LongType

isLong() - Method in class smile.data.type.ObjectType

isLong(DataType) - Static method in interface smile.data.type.DataType

Returns true if the given type is of long, either primitive or boxed.

isMPS() - Method in class smile.deep.tensor.Device

Returns true if the device is MPS.

isNormalized() - Method in class smile.classification.RBFNetwork

Returns true if the model is normalized.

isNormalized() - Method in class smile.regression.RBFNetwork

Returns true if the model is normalized.

isNullAt(int) - Method in interface smile.data.Tuple

Checks whether the value at position i is null.

isNullAt(int) - Method in interface smile.data.vector.Vector

Checks if the value at position i is null.

isNullAt(int, int) - Method in interface smile.data.DataFrame

Checks whether the value at position (i, j) is null.

isNullAt(int, String) - Method in interface smile.data.DataFrame

Checks whether the field value is null.

isNullAt(String) - Method in interface smile.data.Tuple

Checks whether the field value is null.

isNullOrEmpty(String) - Static method in interface smile.util.Strings

Returns true if the string is null or empty.

isNumeric() - Method in interface smile.data.type.DataType

Returns true if the type is numeric (integral or floating).

isNumeric() - Method in class smile.data.type.StructField

Returns true if the field is of integer or floating but not nominal scale.

ISO8601 - Static variable in class smile.swing.table.DateCellEditor

ISO8601 - Static variable in class smile.swing.table.DateCellRenderer

isObject() - Method in interface smile.data.type.DataType

Returns true if the type is ObjectType.

isObject() - Method in class smile.data.type.ObjectType

isObject() - Method in class smile.data.type.StringType

IsolationForest - Class in smile.anomaly

Isolation forest is an unsupervised learning algorithm for anomaly detection that works on the principle of isolating anomalies.

IsolationForest(int, int, IsolationTree...) - Constructor for class smile.anomaly.IsolationForest

Constructor.

IsolationTree - Class in smile.anomaly

Isolation tree.

IsolationTree(List<double[]>, int, int) - Constructor for class smile.anomaly.IsolationTree

Constructor.

Isoline - Class in smile.plot.swing

Contour contains a list of segments.

Isoline(double, boolean) - Constructor for class smile.plot.swing.Isoline

Constructor.

IsoMap - Class in smile.manifold

Isometric feature mapping.

IsoMap(int[], double[][], AdjacencyList) - Constructor for class smile.manifold.IsoMap

Constructor.

IsotonicMDS - Class in smile.manifold

Kruskal's non-metric MDS.

IsotonicMDS(double, double[][]) - Constructor for class smile.manifold.IsotonicMDS

Constructor.

IsotonicRegressionScaling - Class in smile.classification

A method to calibrate decision function value to probability.

IsotonicRegressionScaling(double[], double[]) - Constructor for class smile.classification.IsotonicRegressionScaling

Constructor.

IsotropicKernel - Interface in smile.math.kernel

Isotropic kernel.

isPower2(int) - Static method in class smile.math.MathEx

Returns true if x is a power of 2.

isPrimitive() - Method in interface smile.data.type.DataType

Returns true if this is a primitive data type.

isProbablePrime(long, int) - Static method in class smile.math.MathEx

Returns true if n is probably prime, false if it's definitely composite.

isShiftable() - Method in class smile.neighbor.lsh.Probe

Returns true if the probe is shiftable.

isShort() - Method in interface smile.data.type.DataType

Returns true if the type is short or Short.

isShort() - Method in class smile.data.type.ObjectType

isShort() - Method in class smile.data.type.ShortType

isSingular() - Method in class smile.math.matrix.BandMatrix.LU

Returns true if the matrix is singular.

isSingular() - Method in class smile.math.matrix.BigMatrix.LU

Returns true if the matrix is singular.

isSingular() - Method in class smile.math.matrix.fp32.BandMatrix.LU

Returns true if the matrix is singular.

isSingular() - Method in class smile.math.matrix.fp32.Matrix.LU

Returns true if the matrix is singular.

isSingular() - Method in class smile.math.matrix.fp32.SymmMatrix.BunchKaufman

Returns true if the matrix is singular.

isSingular() - Method in class smile.math.matrix.Matrix.LU

Returns true if the matrix is singular.

isSingular() - Method in class smile.math.matrix.SymmMatrix.BunchKaufman

Returns true if the matrix is singular.

isSpecialTokenAllowed() - Method in class smile.llm.tokenizer.Tiktoken

Returns how special tokens will be encoded.

isString() - Method in interface smile.data.type.DataType

Returns true if the type is String.

isString() - Method in class smile.data.type.StringType

isSymmetric() - Method in class smile.math.matrix.BandMatrix

Return true if the matrix is symmetric (uplo != null).

isSymmetric() - Method in class smile.math.matrix.BigMatrix

Return true if the matrix is symmetric (uplo != null && diag == null).

isSymmetric() - Method in class smile.math.matrix.fp32.BandMatrix

Return true if the matrix is symmetric (uplo != null).

isSymmetric() - Method in class smile.math.matrix.fp32.Matrix

Return true if the matrix is symmetric (uplo != null && diag == null).

isSymmetric() - Method in class smile.math.matrix.Matrix

Return true if the matrix is symmetric (uplo != null && diag == null).

isTickVisible() - Method in class smile.plot.swing.Axis

Returns the visibility of the axis label.

isTraining() - Method in interface smile.deep.layer.Layer

Returns true if the layer is in training mode.

isVariable() - Method in interface smile.data.formula.Feature

Returns true if the term represents a plain variable/column in the data frame.

isZero(double) - Static method in class smile.math.MathEx

Tests if a floating number is zero in machine precision.

isZero(double, double) - Static method in class smile.math.MathEx

Tests if a floating number is zero in given precision.

isZero(float) - Static method in class smile.math.MathEx

Tests if a floating number is zero in machine precision.

isZero(float, float) - Static method in class smile.math.MathEx

Tests if a floating number is zero in given precision.

items - Variable in class smile.association.ItemSet

The set of items.

ItemSet - Class in smile.association

A set of items.

ItemSet(int[], int) - Constructor for class smile.association.ItemSet

Constructor.

iterator() - Method in class smile.association.ARM

iterator() - Method in class smile.association.FPGrowth

iterator() - Method in class smile.data.IndexDataFrame

iterator() - Method in class smile.math.matrix.fp32.SparseMatrix

Returns the iterator of nonzero entries.

iterator() - Method in class smile.math.matrix.SparseMatrix

Returns the iterator of nonzero entries.

iterator() - Method in interface smile.nlp.dictionary.Dictionary

Returns an iterator over the words in this dictionary.

iterator() - Method in enum class smile.nlp.dictionary.EnglishDictionary

iterator() - Method in class smile.nlp.dictionary.EnglishPunctuations

iterator() - Method in enum class smile.nlp.dictionary.EnglishStopWords

iterator() - Method in class smile.nlp.dictionary.SimpleDictionary

iterator() - Method in class smile.util.SparseArray

iterator() - Method in class smile.vision.ImageDataset

iterator(int, int) - Method in class smile.math.matrix.fp32.SparseMatrix

Returns the iterator of nonzero entries.

iterator(int, int) - Method in class smile.math.matrix.SparseMatrix

Returns the iterator of nonzero entries.

iv - Variable in class smile.feature.selection.InformationValue

Information value.

J

j - Variable in class smile.math.matrix.fp32.SparseMatrix.Entry

The column index.

j - Variable in class smile.math.matrix.SparseMatrix.Entry

The column index.

JaccardDistance<T> - Class in smile.math.distance

The Jaccard index, also known as the Jaccard similarity coefficient is a statistic used for comparing the similarity and diversity of sample sets.

JaccardDistance() - Constructor for class smile.math.distance.JaccardDistance

Constructor.

Jacobi() - Method in class smile.math.matrix.fp32.IMatrix

Returns a simple Jacobi preconditioner matrix that is the trivial diagonal part of A in some cases.

Jacobi() - Method in class smile.math.matrix.IMatrix

Returns a simple Jacobi preconditioner matrix that is the trivial diagonal part of A in some cases.

JensenShannonDistance - Class in smile.math.distance

The Jensen-Shannon divergence is a popular method of measuring the similarity between two probability distributions.

JensenShannonDistance() - Constructor for class smile.math.distance.JensenShannonDistance

Constructor.

JensenShannonDivergence(double[], double[]) - Static method in class smile.math.MathEx

Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.

JensenShannonDivergence(double[], SparseArray) - Static method in class smile.math.MathEx

Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.

JensenShannonDivergence(SparseArray, double[]) - Static method in class smile.math.MathEx

Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.

JensenShannonDivergence(SparseArray, SparseArray) - Static method in class smile.math.MathEx

Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.

jet(int) - Static method in interface smile.plot.swing.Palette

Generate jet color palette.

jet(int, float) - Static method in interface smile.plot.swing.Palette

Generate jet color palette.

JJ - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Adjective.

JJR - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Adjective, comparative.

JJS - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Adjective, superlative.

joinAggregate(String, String, String, String...) - Method in class smile.plot.vega.Transform

The join-aggregate transform extends the input data objects with aggregate values in a new field.

joint(int[], int[]) - Static method in class smile.validation.metric.NormalizedMutualInformation

Calculates the normalized mutual information of I(y1, y2) / H(y1, y2).

JOINT - Enum constant in enum class smile.validation.metric.NormalizedMutualInformation.Method

I(y1, y2) / H(y1, y2)

JOINT - Static variable in class smile.validation.metric.NormalizedMutualInformation

Default instance with max normalization.

JointPrediction(T[], double[], double[], Matrix) - Constructor for class smile.regression.GaussianProcessRegression.JointPrediction

Constructor.

json(String) - Static method in interface smile.io.Read

Reads a JSON file.

json(String, String) - Method in class smile.plot.vega.Data

Loads a JSON file.

json(String, String...) - Method in class smile.data.SQL

Creates an in-memory table from json files.

json(String, String, Map<String, String>, String...) - Method in class smile.data.SQL

Creates an in-memory table from json files.

json(String, JSON.Mode, StructType) - Static method in interface smile.io.Read

Reads a JSON file.

json(Path) - Static method in interface smile.io.Read

Reads a JSON file.

json(Path, JSON.Mode, StructType) - Static method in interface smile.io.Read

Reads a JSON file.

JSON - Class in smile.io

Reads JSON datasets.

JSON() - Constructor for class smile.io.JSON

Constructor.

JSON.Mode - Enum Class in smile.io

JSON files in single-line or multi-line mode.

K

k - Variable in class smile.classification.ClassLabels

The number of classes.

k - Variable in class smile.clustering.PartitionClustering

The number of clusters.

k - Variable in class smile.neighbor.LSH

The number of random projections per hash value.

k - Variable in class smile.stat.distribution.GammaDistribution

The shape parameter.

k - Variable in class smile.stat.distribution.WeibullDistribution

The shape parameter.

k(double) - Method in class smile.math.kernel.BinarySparseLinearKernel

k(double) - Method in interface smile.math.kernel.DotProductKernel

Computes the dot product kernel function.

k(double) - Method in class smile.math.kernel.Gaussian

k(double) - Method in class smile.math.kernel.HyperbolicTangent

k(double) - Method in interface smile.math.kernel.IsotropicKernel

Computes the isotropic kernel function.

k(double) - Method in class smile.math.kernel.Laplacian

k(double) - Method in class smile.math.kernel.LinearKernel

k(double) - Method in class smile.math.kernel.Matern

k(double) - Method in class smile.math.kernel.Polynomial

k(double) - Method in class smile.math.kernel.SparseLinearKernel

k(double) - Method in class smile.math.kernel.ThinPlateSpline

k(double[], double[]) - Method in class smile.math.kernel.GaussianKernel

k(double[], double[]) - Method in class smile.math.kernel.HellingerKernel

k(double[], double[]) - Method in class smile.math.kernel.HyperbolicTangentKernel

k(double[], double[]) - Method in class smile.math.kernel.LaplacianKernel

k(double[], double[]) - Method in class smile.math.kernel.LinearKernel

k(double[], double[]) - Method in class smile.math.kernel.MaternKernel

k(double[], double[]) - Method in class smile.math.kernel.PearsonKernel

k(double[], double[]) - Method in class smile.math.kernel.PolynomialKernel

k(double[], double[]) - Method in class smile.math.kernel.ThinPlateSplineKernel

k(int[], int[]) - Method in class smile.math.kernel.BinarySparseGaussianKernel

k(int[], int[]) - Method in class smile.math.kernel.BinarySparseHyperbolicTangentKernel

k(int[], int[]) - Method in class smile.math.kernel.BinarySparseLaplacianKernel

k(int[], int[]) - Method in class smile.math.kernel.BinarySparseLinearKernel

k(int[], int[]) - Method in class smile.math.kernel.BinarySparseMaternKernel

k(int[], int[]) - Method in class smile.math.kernel.BinarySparsePolynomialKernel

k(int[], int[]) - Method in class smile.math.kernel.BinarySparseThinPlateSplineKernel

k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseGaussianKernel

k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseHyperbolicTangentKernel

k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseLaplacianKernel

k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseLinearKernel

k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseMaternKernel

k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparsePolynomialKernel

k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseThinPlateSplineKernel

k(T, T) - Method in interface smile.math.kernel.MercerKernel

Kernel function.

k(T, T) - Method in class smile.math.kernel.ProductKernel

k(T, T) - Method in class smile.math.kernel.SumKernel

K(Matrix) - Method in interface smile.math.kernel.DotProductKernel

Computes the kernel matrix.

K(Matrix) - Method in interface smile.math.kernel.IsotropicKernel

Computes the kernel matrix.

K(T[]) - Method in interface smile.math.kernel.MercerKernel

Computes the kernel matrix.

K(T[], T[]) - Method in interface smile.math.kernel.MercerKernel

Returns the kernel matrix.

KDTree<E> - Class in smile.neighbor

A KD-tree (short for k-dimensional tree) is a space-partitioning dataset structure for organizing points in a k-dimensional space.

KDTree(double[][], E[]) - Constructor for class smile.neighbor.KDTree

Constructor.

kendall(double[], double[]) - Static method in class smile.math.MathEx

The Kendall Tau Rank Correlation Coefficient is used to measure the degree of correspondence between sets of rankings where the measures are not equidistant.

kendall(double[], double[]) - Static method in class smile.stat.hypothesis.CorTest

Kendall rank correlation test.

kendall(float[], float[]) - Static method in class smile.math.MathEx

The Kendall Tau Rank Correlation Coefficient is used to measure the degree of correspondence between sets of rankings where the measures are not equidistant.

kendall(int[], int[]) - Static method in class smile.math.MathEx

The Kendall Tau Rank Correlation Coefficient is used to measure the degree of correspondence between sets of rankings where the measures are not equidistant.

kernel - Variable in class smile.regression.GaussianProcessRegression

The covariance/kernel function.

kernel() - Method in class smile.base.svm.KernelMachine

Returns the kernel function.

kernel() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns the value of the kernel record component.

kernel() - Method in record class smile.vision.layer.MBConvConfig

Returns the value of the kernel record component.

KernelDensity - Class in smile.stat.distribution

Kernel density estimation is a non-parametric way of estimating the probability density function of a random variable.

KernelDensity(double[]) - Constructor for class smile.stat.distribution.KernelDensity

Constructor.

KernelDensity(double[], double) - Constructor for class smile.stat.distribution.KernelDensity

Constructor.

KernelMachine<T> - Class in smile.base.svm

Kernel machines.

KernelMachine<T> - Class in smile.regression

The learning methods building on kernels.

KernelMachine(MercerKernel<T>, T[], double[]) - Constructor for class smile.base.svm.KernelMachine

Constructor.

KernelMachine(MercerKernel<T>, T[], double[]) - Constructor for class smile.regression.KernelMachine

Constructor.

KernelMachine(MercerKernel<T>, T[], double[], double) - Constructor for class smile.base.svm.KernelMachine

Constructor.

KernelMachine(MercerKernel<T>, T[], double[], double) - Constructor for class smile.regression.KernelMachine

Constructor.

KernelPCA - Class in smile.feature.extraction

Kernel PCA transform.

KernelPCA(KPCA<double[]>, String...) - Constructor for class smile.feature.extraction.KernelPCA

Constructor.

key - Variable in class smile.neighbor.Neighbor

The key of neighbor.

keys - Variable in class smile.neighbor.LSH

The object keys.

keys() - Method in class smile.neighbor.MutableLSH

Returns the keys.

keyvals(double[]) - Method in class smile.plot.vega.ImputeTransform

Sets the key values that should be considered for imputation.

keyvals(double, double, double) - Method in class smile.plot.vega.ImputeTransform

Sets the sequence of key values that should be considered for imputation.

keywords() - Method in class smile.taxonomy.Concept

Returns the concept synonym set.

kg(double) - Method in class smile.math.kernel.BinarySparseLinearKernel

kg(double) - Method in interface smile.math.kernel.DotProductKernel

Computes the dot product kernel function and its gradient over hyperparameters..

kg(double) - Method in class smile.math.kernel.Gaussian

kg(double) - Method in class smile.math.kernel.HyperbolicTangent

kg(double) - Method in interface smile.math.kernel.IsotropicKernel

Computes the isotropic kernel function and its gradient over hyperparameters..

kg(double) - Method in class smile.math.kernel.Laplacian

kg(double) - Method in class smile.math.kernel.LinearKernel

kg(double) - Method in class smile.math.kernel.Matern

kg(double) - Method in class smile.math.kernel.Polynomial

kg(double) - Method in class smile.math.kernel.SparseLinearKernel

kg(double) - Method in class smile.math.kernel.ThinPlateSpline

kg(double[], double[]) - Method in class smile.math.kernel.GaussianKernel

kg(double[], double[]) - Method in class smile.math.kernel.HellingerKernel

kg(double[], double[]) - Method in class smile.math.kernel.HyperbolicTangentKernel

kg(double[], double[]) - Method in class smile.math.kernel.LaplacianKernel

kg(double[], double[]) - Method in class smile.math.kernel.LinearKernel

kg(double[], double[]) - Method in class smile.math.kernel.MaternKernel

kg(double[], double[]) - Method in class smile.math.kernel.PearsonKernel

kg(double[], double[]) - Method in class smile.math.kernel.PolynomialKernel

kg(double[], double[]) - Method in class smile.math.kernel.ThinPlateSplineKernel

kg(int[], int[]) - Method in class smile.math.kernel.BinarySparseGaussianKernel

kg(int[], int[]) - Method in class smile.math.kernel.BinarySparseHyperbolicTangentKernel

kg(int[], int[]) - Method in class smile.math.kernel.BinarySparseLaplacianKernel

kg(int[], int[]) - Method in class smile.math.kernel.BinarySparseLinearKernel

kg(int[], int[]) - Method in class smile.math.kernel.BinarySparseMaternKernel

kg(int[], int[]) - Method in class smile.math.kernel.BinarySparsePolynomialKernel

kg(int[], int[]) - Method in class smile.math.kernel.BinarySparseThinPlateSplineKernel

kg(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseGaussianKernel

kg(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseHyperbolicTangentKernel

kg(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseLaplacianKernel

kg(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseLinearKernel

kg(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseMaternKernel

kg(SparseArray, SparseArray) - Method in class smile.math.kernel.SparsePolynomialKernel

kg(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseThinPlateSplineKernel

kg(T, T) - Method in interface smile.math.kernel.MercerKernel

Computes the kernel and its gradient over hyperparameters.

kg(T, T) - Method in class smile.math.kernel.ProductKernel

kg(T, T) - Method in class smile.math.kernel.SumKernel

KG(Matrix) - Method in interface smile.math.kernel.IsotropicKernel

Computes the kernel and gradient matrices.

KG(T[]) - Method in interface smile.math.kernel.MercerKernel

Computes the kernel and gradient matrices.

kl() - Static method in interface smile.deep.Loss

Kullback-Leibler Divergence Loss Function.

kl() - Method in class smile.math.matrix.BandMatrix

Returns the number of subdiagonals.

kl() - Method in class smile.math.matrix.fp32.BandMatrix

Returns the number of subdiagonals.

KMeans - Class in smile.clustering

K-Means clustering.

KMeans(double, double[][], int[]) - Constructor for class smile.clustering.KMeans

Constructor.

KMedoidsImputer - Class in smile.feature.imputation

Missing value imputation by K-Medoids clustering.

KMedoidsImputer(CLARANS<Tuple>) - Constructor for class smile.feature.imputation.KMedoidsImputer

Constructor.

KModes - Class in smile.clustering

K-Modes clustering.

KModes(double, int[][], int[]) - Constructor for class smile.clustering.KModes

Constructor.

KNN<T> - Class in smile.classification

K-nearest neighbor classifier.

KNN(KNNSearch<T, T>, int[], int) - Constructor for class smile.classification.KNN

Constructor.

KNNImputer - Class in smile.feature.imputation

Missing value imputation with k-nearest neighbors.

KNNImputer(DataFrame, int, String...) - Constructor for class smile.feature.imputation.KNNImputer

Constructor with Euclidean distance on selected columns.

KNNImputer(DataFrame, int, Distance<Tuple>) - Constructor for class smile.feature.imputation.KNNImputer

Constructor.

KNNSearch<K,V> - Interface in smile.neighbor

Retrieves the top k nearest neighbors to the query.

kpca - Variable in class smile.feature.extraction.KernelPCA

Kernel PCA.

KPCA<T> - Class in smile.manifold

Kernel principal component analysis.

KPCA(T[], MercerKernel<T>, double[], double, double[][], double[], Matrix) - Constructor for class smile.manifold.KPCA

Constructor.

KrigingInterpolation - Class in smile.interpolation

Kriging interpolation for the data points irregularly distributed in space.

KrigingInterpolation(double[][], double[]) - Constructor for class smile.interpolation.KrigingInterpolation

Constructor.

KrigingInterpolation(double[][], double[], Variogram, double[]) - Constructor for class smile.interpolation.KrigingInterpolation

Constructor.

KrigingInterpolation1D - Class in smile.interpolation

Kriging interpolation for the data points irregularly distributed in space.

KrigingInterpolation1D(double[], double[]) - Constructor for class smile.interpolation.KrigingInterpolation1D

Constructor.

KrigingInterpolation1D(double[], double[], double) - Constructor for class smile.interpolation.KrigingInterpolation1D

Constructor.

KrigingInterpolation2D - Class in smile.interpolation

Kriging interpolation for the data points irregularly distributed in space.

KrigingInterpolation2D(double[], double[], double[]) - Constructor for class smile.interpolation.KrigingInterpolation2D

Constructor.

KrigingInterpolation2D(double[], double[], double[], double) - Constructor for class smile.interpolation.KrigingInterpolation2D

Constructor.

KSTest - Class in smile.stat.hypothesis

The Kolmogorov-Smirnov test (K-S test) is a form of minimum distance estimation used as a non-parametric test of equality of one-dimensional probability distributions.

KSTest(String, double, double) - Constructor for class smile.stat.hypothesis.KSTest

Constructor.

ku() - Method in class smile.math.matrix.BandMatrix

Returns the number of superdiagonals.

ku() - Method in class smile.math.matrix.fp32.BandMatrix

Returns the number of superdiagonals.

KullbackLeiblerDivergence(double[], double[]) - Static method in class smile.math.MathEx

Kullback-Leibler divergence.

KullbackLeiblerDivergence(double[], SparseArray) - Static method in class smile.math.MathEx

Kullback-Leibler divergence.

KullbackLeiblerDivergence(SparseArray, double[]) - Static method in class smile.math.MathEx

Kullback-Leibler divergence.

KullbackLeiblerDivergence(SparseArray, SparseArray) - Static method in class smile.math.MathEx

Kullback-Leibler divergence.

Kurtosis - Class in smile.ica

The kurtosis of the probability density function of a signal.

Kurtosis() - Constructor for class smile.ica.Kurtosis

L

L - Variable in class smile.regression.GaussianProcessRegression

The log marginal likelihood, which may be not available (NaN) when the model is fit with approximate methods.

L - Variable in class smile.stat.distribution.DiscreteExponentialFamilyMixture

The log-likelihood when the distribution is fit on a sample data.

L - Variable in class smile.stat.distribution.ExponentialFamilyMixture

The log-likelihood when the distribution is fit on a sample data.

L - Variable in class smile.stat.distribution.MultivariateExponentialFamilyMixture

The log-likelihood when the distribution is fit on a sample data.

L - Variable in class smile.vq.BIRCH

The number of CF entries in the leaf nodes.

L_INF - Enum constant in enum class smile.feature.transform.Normalizer.Norm

Normalize L-infinity vector norm.

l1() - Static method in interface smile.deep.Loss

Mean Absolute Error (L1) Loss Function.

L1 - Enum constant in enum class smile.feature.transform.Normalizer.Norm

Normalize L1 vector norm.

L2 - Enum constant in enum class smile.feature.transform.Normalizer.Norm

Normalize L2 vector norm.

LA - Enum constant in enum class smile.math.matrix.ARPACK.SymmOption

The largest algebraic eigenvalues.

LA - Enum constant in enum class smile.math.matrix.fp32.ARPACK.SymmOption

The largest algebraic eigenvalues.

Label - Class in smile.plot.swing

Label is a single line text.

Label(String, double[], double, double, double, Font, Color) - Constructor for class smile.plot.swing.Label

Constructor.

label2Id - Static variable in interface smile.vision.ImageNet

The map from label to class id.

label2Target - Static variable in interface smile.vision.ImageNet

The functor mapping label to class id.

labelAlign(String) - Method in class smile.plot.vega.Axis

Sets the horizontal text alignment of axis tick labels.

labelAlign(String) - Method in class smile.plot.vega.Legend

Sets the alignment of the legend label.

labelAngle(double) - Method in class smile.plot.vega.Axis

Sets the rotation angle of the axis labels.

labelBaseline(String) - Method in class smile.plot.vega.Axis

Sets the vertical text baseline of axis tick labels.

labelBaseline(String) - Method in class smile.plot.vega.Legend

Sets the position of the baseline of legend label.

labelBound(boolean) - Method in class smile.plot.vega.Axis

Sets if labels should be hidden if they exceed the axis range.

labelBound(double) - Method in class smile.plot.vega.Axis

Sets the pixel tolerance of label bounding box.

labelColor(String) - Method in class smile.plot.vega.Axis

Sets the color of the tick label.

labelColor(String) - Method in class smile.plot.vega.Legend

Sets the color of the legend label.

labelExpr(String) - Method in class smile.plot.vega.Axis

Sets the Vega expression for customizing labels.

labelExpr(String) - Method in class smile.plot.vega.Legend

Sets the Vega expression for customizing labels.

labelFlush(boolean) - Method in class smile.plot.vega.Axis

Sets if the first and last axis labels should be aligned flush with the scale range.

labelFlush(double) - Method in class smile.plot.vega.Axis

Sets the number of pixels by which to offset the first and last labels.

labelFlushOffset(double) - Method in class smile.plot.vega.Axis

Sets the number of pixels by which to offset flush-adjusted labels.

labelFont(String) - Method in class smile.plot.vega.Axis

Sets the font of the tick label.

labelFont(String) - Method in class smile.plot.vega.Legend

Sets the font of the legend label.

labelFontSize(double) - Method in class smile.plot.vega.Axis

Sets the font size of the label in pixels.

labelFontSize(double) - Method in class smile.plot.vega.Legend

Sets the font size of the label in pixels.

labelFontStyle(String) - Method in class smile.plot.vega.Axis

Sets the font style of the title.

labelFontStyle(String) - Method in class smile.plot.vega.Legend

Sets the font style of the title.

labelFontWeight(int) - Method in class smile.plot.vega.Axis

Sets the font weight of axis tick labels.

labelFontWeight(int) - Method in class smile.plot.vega.Legend

Sets the font weight of legend labels.

labelFontWeight(String) - Method in class smile.plot.vega.Axis

Sets the font weight of axis tick labels.

labelFontWeight(String) - Method in class smile.plot.vega.Legend

Sets the font weight of legend labels.

labelLimit(int) - Method in class smile.plot.vega.Axis

Sets the maximum allowed pixel width of axis tick labels.

labelLimit(int) - Method in class smile.plot.vega.Legend

Sets the maximum allowed pixel width of legend labels.

labelLineHeight(int) - Method in class smile.plot.vega.Axis

Sets the line height in pixels for multi-line label text.

labelLineHeight(String) - Method in class smile.plot.vega.Axis

Sets the line height for multi-line label text.

labelOffset(int) - Method in class smile.plot.vega.Axis

Sets the position offset in pixels to apply to labels, in addition to tickOffset.

labelOffset(int) - Method in class smile.plot.vega.Legend

Sets the position offset in pixels to apply to labels.

labelOpacity(double) - Method in class smile.plot.vega.Axis

Sets the opacity of the labels.

labelOverlap(boolean) - Method in class smile.plot.vega.Axis

Sets the strategy to use for resolving overlap of axis labels.

labelOverlap(boolean) - Method in class smile.plot.vega.Legend

Sets the strategy to use for resolving overlap of legend labels.

labelOverlap(String) - Method in class smile.plot.vega.Axis

Sets the strategy to use for resolving overlap of axis labels.

labelOverlap(String) - Method in class smile.plot.vega.Legend

Sets the strategy to use for resolving overlap of legend labels.

labelPadding(double) - Method in class smile.plot.vega.Axis

Sets the padding in pixels between labels and ticks.

labels - Static variable in interface smile.vision.ImageNet

Class labels.

labels(boolean) - Method in class smile.plot.vega.Axis

Sets if labels should be included as part of the axis.

labelSeparation(double) - Method in class smile.plot.vega.Axis

Sets the minimum separation that must be between label bounding boxes for them to be considered non-overlapping (default 0).

lad() - Static method in interface smile.base.cart.Loss

Least absolute deviation regression loss.

LamarckianChromosome - Interface in smile.gap

Artificial chromosomes used in Lamarckian algorithm that is a hybrid of of evolutionary computation and a local improver such as hill-climbing.

lambda - Variable in class smile.base.mlp.MultilayerPerceptron

The L2 regularization factor, which is also the weight decay factor.

lambda - Variable in class smile.stat.distribution.ExponentialDistribution

The rate parameter.

lambda - Variable in class smile.stat.distribution.PoissonDistribution

The average number of events per interval.

lambda - Variable in class smile.stat.distribution.WeibullDistribution

The scale parameter.

LancasterStemmer - Class in smile.nlp.stemmer

The Paice/Husk Lancaster stemming algorithm.

LancasterStemmer() - Constructor for class smile.nlp.stemmer.LancasterStemmer

Constructor with default rules.

LancasterStemmer(boolean) - Constructor for class smile.nlp.stemmer.LancasterStemmer

Constructor with default rules.

LancasterStemmer(InputStream) - Constructor for class smile.nlp.stemmer.LancasterStemmer

Constructor with customized rules.

LancasterStemmer(InputStream, boolean) - Constructor for class smile.nlp.stemmer.LancasterStemmer

Constructor with customized rules.

Lanczos - Class in smile.math.matrix

The Lanczos algorithm is a direct algorithm devised by Cornelius Lanczos that is an adaptation of power methods to find the most useful eigenvalues and eigenvectors of an n^th order linear system with a limited number of operations, m, where m is much smaller than n.

Lanczos() - Constructor for class smile.math.matrix.Lanczos

lapack() - Method in enum class smile.math.blas.Diag

Returns the value for LAPACK.

lapack() - Method in enum class smile.math.blas.EigenRange

Returns the byte value for LAPACK.

lapack() - Method in enum class smile.math.blas.EVDJob

Returns the byte value for LAPACK.

lapack() - Method in enum class smile.math.blas.Layout

Returns the byte value for LAPACK.

lapack() - Method in enum class smile.math.blas.Side

Returns the byte value for LAPACK.

lapack() - Method in enum class smile.math.blas.SVDJob

Returns the byte value for LAPACK.

lapack() - Method in enum class smile.math.blas.Transpose

Returns the byte value for LAPACK.

lapack() - Method in enum class smile.math.blas.UPLO

Returns the byte value for LAPACK.

LAPACK - Interface in smile.math.blas

Linear Algebra Package.

LaplaceInterpolation - Class in smile.interpolation

Laplace interpolation to restore missing or unmeasured values on a 2-dimensional evenly spaced regular grid.

LaplaceInterpolation() - Constructor for class smile.interpolation.LaplaceInterpolation

Laplacian - Class in smile.math.kernel

Laplacian kernel, also referred as exponential kernel.

Laplacian(double, double, double) - Constructor for class smile.math.kernel.Laplacian

Constructor.

LaplacianEigenmap - Class in smile.manifold

Laplacian Eigenmap.

LaplacianEigenmap(double, int[], double[][], AdjacencyList) - Constructor for class smile.manifold.LaplacianEigenmap

Constructor with Gaussian kernel.

LaplacianEigenmap(int[], double[][], AdjacencyList) - Constructor for class smile.manifold.LaplacianEigenmap

Constructor with discrete weights.

LaplacianKernel - Class in smile.math.kernel

Laplacian kernel, also referred as exponential kernel.

LaplacianKernel(double) - Constructor for class smile.math.kernel.LaplacianKernel

Constructor.

LaplacianKernel(double, double, double) - Constructor for class smile.math.kernel.LaplacianKernel

Constructor.

LASSO - Class in smile.regression

Lasso (least absolute shrinkage and selection operator) regression.

LASSO() - Constructor for class smile.regression.LASSO

LASVM<T> - Class in smile.base.svm

LASVM is an approximate SVM solver that uses online approximation.

LASVM(MercerKernel<T>, double, double) - Constructor for class smile.base.svm.LASVM

Constructor.

LASVM(MercerKernel<T>, double, double, double) - Constructor for class smile.base.svm.LASVM

Constructor.

latin(int, int) - Static method in interface smile.stat.Sampling

Latin hypercube sampling.

lattice(int, int, double[][]) - Static method in class smile.vq.SOM

Creates a lattice of which the weight vectors are randomly selected from samples.

Layer - Class in smile.base.mlp

A layer in the neural network.

Layer - Class in smile.plot.vega

To superimpose one chart on top of another.

Layer - Interface in smile.deep.layer

A layer in the neural network.

Layer(int, int) - Constructor for class smile.base.mlp.Layer

Constructor.

Layer(int, int, double) - Constructor for class smile.base.mlp.Layer

Constructor.

Layer(Matrix, double[]) - Constructor for class smile.base.mlp.Layer

Constructor.

Layer(Matrix, double[], double) - Constructor for class smile.base.mlp.Layer

Constructor.

Layer(View...) - Constructor for class smile.plot.vega.Layer

Constructor.

LayerBlock - Class in smile.deep.layer

A block is combinations of one or more layers.

LayerBlock() - Constructor for class smile.deep.layer.LayerBlock

Constructor.

LayerBlock(String) - Constructor for class smile.deep.layer.LayerBlock

Constructor.

LayerBlock(Module) - Constructor for class smile.deep.layer.LayerBlock

Constructor.

LayerBuilder - Class in smile.base.mlp

The builder of layers.

LayerBuilder(int, double) - Constructor for class smile.base.mlp.LayerBuilder

Constructor.

layout() - Method in class smile.math.matrix.BandMatrix

Returns the matrix layout.

layout() - Method in class smile.math.matrix.BigMatrix

Returns the matrix layout.

layout() - Method in class smile.math.matrix.fp32.BandMatrix

Returns the matrix layout.

layout() - Method in class smile.math.matrix.fp32.Matrix

Returns the matrix layout.

layout() - Method in class smile.math.matrix.fp32.SymmMatrix

Returns the matrix layout.

layout() - Method in class smile.math.matrix.Matrix

Returns the matrix layout.

layout() - Method in class smile.math.matrix.SymmMatrix

Returns the matrix layout.

layout(Layout) - Method in class smile.deep.tensor.Tensor.Options

Sets strided (dense) or sparse tensor.

Layout - Enum Class in smile.deep.tensor

The memory layout of a Tensor.

Layout - Enum Class in smile.math.blas

Matrix layout.

lchoose(int, int) - Static method in class smile.math.MathEx

The log of n choose k.

ld() - Method in class smile.math.matrix.BandMatrix

Returns the leading dimension.

ld() - Method in class smile.math.matrix.BigMatrix

Returns the leading dimension.

ld() - Method in class smile.math.matrix.fp32.BandMatrix

Returns the leading dimension.

ld() - Method in class smile.math.matrix.fp32.Matrix

Returns the leading dimension.

ld() - Method in class smile.math.matrix.Matrix

Returns the leading dimension.

LDA - Class in smile.classification

Linear discriminant analysis.

LDA(double[], double[][], double[], Matrix) - Constructor for class smile.classification.LDA

Constructor.

LDA(double[], double[][], double[], Matrix, IntSet) - Constructor for class smile.classification.LDA

Constructor.

le(double) - Method in class smile.deep.tensor.Tensor

Computes element-wise less-than-or-equal-to comparison.

le(int) - Method in class smile.deep.tensor.Tensor

Computes element-wise less-than-or-equal-to comparison.

le(Tensor) - Method in class smile.deep.tensor.Tensor

Computes element-wise less-than-or-equal-to comparison.

LeafNode - Class in smile.base.cart

A leaf node in decision tree.

LeafNode(int) - Constructor for class smile.base.cart.LeafNode

Constructor.

leaky() - Static method in interface smile.base.mlp.activation.ActivationFunction

Returns the leaky rectifier activation function max(x, 0.01x).

leaky() - Static method in interface smile.base.mlp.ActivationFunction

The leaky rectifier activation function max(x, 0.01x).

leaky(double) - Static method in interface smile.base.mlp.activation.ActivationFunction

Returns the leaky rectifier activation function max(x, ax) where 0 <= a < 1.

leaky(double) - Static method in interface smile.base.mlp.ActivationFunction

The leaky rectifier activation function max(x, ax) where 0 <= a < 1.

leaky(int) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with leaky rectified linear activation function.

leaky(int, double) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with leaky rectified linear activation function.

leaky(int, double, double) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with leaky rectified linear activation function.

leaky(int, int, double) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with leaky ReLU activation function.

leaky(int, int, double, double) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with leaky ReLU activation function.

LeakyReLU - Class in smile.base.mlp.activation

The leaky rectifier activation function max(x, ax) where 0 <= a < 1.

LeakyReLU - Class in smile.deep.activation

Sigmoid Linear Unit activation function.

LeakyReLU() - Constructor for class smile.deep.activation.LeakyReLU

Constructor.

LeakyReLU(double) - Constructor for class smile.base.mlp.activation.LeakyReLU

Constructor.

LeakyReLU(double, boolean) - Constructor for class smile.deep.activation.LeakyReLU

Constructor.

learningRate - Variable in class smile.base.mlp.MultilayerPerceptron

The learning rate.

LeastAbsoluteDeviation - Enum constant in enum class smile.base.cart.Loss.Type

Least absolute deviation regression.

LeastSquares - Enum constant in enum class smile.base.cart.Loss.Type

Least squares regression.

leaves() - Method in class smile.base.cart.InternalNode

leaves() - Method in class smile.base.cart.LeafNode

leaves() - Method in interface smile.base.cart.Node

Returns the number of leaf nodes in the subtree.

LeeDistance - Class in smile.math.distance

In coding theory, the Lee distance is a distance between two strings x1x2...xn and y1y2...yn of equal length n over the q-ary alphabet {0, 1, ..., q-1} of size q >= 2, defined as

LeeDistance(int) - Constructor for class smile.math.distance.LeeDistance

Constructor with a given size q of alphabet.

LEFT - Enum constant in enum class smile.math.blas.Side

A * B

leftPad(String, int, char) - Static method in interface smile.util.Strings

Left pad a string with a specified character.

legend() - Method in class smile.plot.vega.Config

Returns the legend definition object.

legend() - Method in class smile.plot.vega.Field

Returns the legend definition object.

Legend - Class in smile.plot.swing

Legend is a single line text which coordinates are in proportional to the base coordinates.

Legend - Class in smile.plot.vega

Similar to axes, legends visualize scales.

Legend(String, Color) - Constructor for class smile.plot.swing.Legend

Constructor.

legends() - Method in class smile.plot.swing.BarPlot

legends() - Method in class smile.plot.swing.LinePlot

legends() - Method in class smile.plot.swing.Plot

Returns the optional name of shape, which will be used to draw a legend outside the box.

legends() - Method in class smile.plot.swing.ScatterPlot

legends() - Method in class smile.plot.swing.ScreePlot

length - Variable in class smile.math.Complex.Array

The length of array.

length() - Method in interface smile.data.BinarySparseDataset

Returns the number of nonzero entries.

length() - Method in interface smile.data.Tuple

Returns the number of elements in the Tuple.

length() - Method in class smile.data.type.StructType

Returns the number of fields.

length() - Method in class smile.gap.BitString

Returns the length of bit string.

length() - Method in class smile.stat.distribution.BernoulliDistribution

length() - Method in class smile.stat.distribution.BetaDistribution

length() - Method in class smile.stat.distribution.BinomialDistribution

length() - Method in class smile.stat.distribution.ChiSquareDistribution

length() - Method in class smile.stat.distribution.DiscreteMixture

length() - Method in interface smile.stat.distribution.Distribution

Returns the number of parameters of the distribution.

length() - Method in class smile.stat.distribution.EmpiricalDistribution

length() - Method in class smile.stat.distribution.ExponentialDistribution

length() - Method in class smile.stat.distribution.FDistribution

length() - Method in class smile.stat.distribution.GammaDistribution

length() - Method in class smile.stat.distribution.GaussianDistribution

length() - Method in class smile.stat.distribution.GeometricDistribution

length() - Method in class smile.stat.distribution.HyperGeometricDistribution

length() - Method in class smile.stat.distribution.KernelDensity

length() - Method in class smile.stat.distribution.LogisticDistribution

length() - Method in class smile.stat.distribution.LogNormalDistribution

length() - Method in class smile.stat.distribution.Mixture

length() - Method in interface smile.stat.distribution.MultivariateDistribution

The number of parameters of the distribution.

length() - Method in class smile.stat.distribution.MultivariateGaussianDistribution

length() - Method in class smile.stat.distribution.MultivariateMixture

length() - Method in class smile.stat.distribution.NegativeBinomialDistribution

length() - Method in class smile.stat.distribution.PoissonDistribution

length() - Method in class smile.stat.distribution.ShiftedGeometricDistribution

length() - Method in class smile.stat.distribution.TDistribution

length() - Method in class smile.stat.distribution.WeibullDistribution

length() - Method in record class smile.util.Bytes

Returns the length of byte string.

level(int) - Method in class smile.data.measure.CategoricalMeasure

Returns the level string representation.

LEVEL - Enum constant in enum class smile.data.CategoricalEncoder

Level of measurement.

levels() - Method in class smile.data.measure.CategoricalMeasure

Returns the levels.

LevenbergMarquardt - Class in smile.math

The Levenberg–Marquardt algorithm.

levenshtein(char[], char[]) - Static method in class smile.math.distance.EditDistance

Levenshtein distance between two strings allows insertion, deletion, or substitution of characters.

levenshtein(String, String) - Static method in class smile.math.distance.EditDistance

Levenshtein distance between two strings allows insertion, deletion, or substitution of characters.

leverage - Variable in class smile.association.AssociationRule

The difference between the probability of the rule and the expected probability if the items were statistically independent.

lfactorial(int) - Static method in class smile.math.MathEx

The log of factorial of n.

lgamma(double) - Static method in class smile.math.special.Gamma

The log of the Gamma function.

lhs(String) - Static method in class smile.data.formula.Formula

Factory method.

lhs(Term) - Static method in class smile.data.formula.Formula

Factory method.

LI - Enum constant in enum class smile.math.matrix.ARPACK.AsymmOption

The eigenvalues of largest imaginary part.

LI - Enum constant in enum class smile.math.matrix.fp32.ARPACK.AsymmOption

The eigenvalues of largest imaginary part.

libsvm(BufferedReader) - Static method in interface smile.io.Read

Reads a libsvm sparse dataset.

libsvm(String) - Static method in interface smile.io.Read

Reads a libsvm sparse dataset.

libsvm(Path) - Static method in interface smile.io.Read

Reads a libsvm sparse dataset.

lift - Variable in class smile.association.AssociationRule

How many times more often antecedent and consequent occur together than expected if they were statistically independent.

LIGHT_GRAY - Static variable in interface smile.plot.swing.Palette

LIGHT_GREEN - Static variable in interface smile.plot.swing.Palette

LIGHT_PURPLE - Static variable in interface smile.plot.swing.Palette

LIGHT_SLATE_GRAY - Static variable in interface smile.plot.swing.Palette

likelihood(double[]) - Method in interface smile.stat.distribution.Distribution

The likelihood of the sample set following this distribution.

likelihood(double[]) - Method in class smile.stat.distribution.KernelDensity

The likelihood of the samples.

likelihood(double[][]) - Method in interface smile.stat.distribution.MultivariateDistribution

The likelihood of the sample set following this distribution.

likelihood(int[]) - Method in class smile.stat.distribution.DiscreteDistribution

The likelihood given a sample set following the distribution.

LIKELIHOOD - Enum constant in enum class smile.base.mlp.Cost

Negative likelihood (or log-likelihood) cost.

limit(double) - Method in class smile.plot.vega.PivotTransform

Sets the maximum number of pivoted fields to generate.

line(boolean) - Method in class smile.plot.vega.Mark

Sets whether the line mark is shown.

Line - Class in smile.plot.swing

This class represents a poly line in the plot.

Line(double[][], Line.Style, char, Color) - Constructor for class smile.plot.swing.Line

Constructor.

Line.Style - Enum Class in smile.plot.swing

The supported styles of lines.

linear() - Static method in interface smile.base.mlp.ActivationFunction

Linear/Identity activation function.

linear(double, double, double) - Static method in interface smile.math.TimeFunction

Returns the linear learning rate decay function that starts with an initial learning rate and reach an end learning rate in the given decay steps..

linear(int) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with linear activation function.

linear(int, double) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with linear activation function.

linear(int, int) - Static method in interface smile.deep.layer.Layer

Returns a linear fully connected layer.

LINEAR - Enum constant in enum class smile.base.mlp.OutputFunction

Linear/Identity function.

LinearInterpolation - Class in smile.interpolation

Piecewise linear interpolation.

LinearInterpolation(double[], double[]) - Constructor for class smile.interpolation.LinearInterpolation

Constructor.

LinearKernel - Class in smile.math.kernel

The linear dot product kernel.

LinearKernel() - Constructor for class smile.math.kernel.LinearKernel

Constructor.

LinearKernelMachine - Class in smile.base.svm

Linear kernel machine.

LinearKernelMachine(double[], double) - Constructor for class smile.base.svm.LinearKernelMachine

Constructor.

LinearModel - Class in smile.regression

Linear model.

LinearModel(Formula, StructType, Matrix, double[], double[], double) - Constructor for class smile.regression.LinearModel

Constructor.

LinearSearch<K,V> - Class in smile.neighbor

Brute force linear nearest neighbor search.

LinearSearch(List<K>, List<V>, Distance<K>) - Constructor for class smile.neighbor.LinearSearch

Constructor.

LinearSearch(List<V>, Distance<K>, Function<V, K>) - Constructor for class smile.neighbor.LinearSearch

Constructor.

LinearSearch(K[], V[], Distance<K>) - Constructor for class smile.neighbor.LinearSearch

Constructor.

LinearSearch(V[], Distance<K>, Function<V, K>) - Constructor for class smile.neighbor.LinearSearch

Constructor.

lineBreak(String) - Method in class smile.plot.vega.Config

Sets a delimiter, such as a newline character, upon which to break text strings into multiple lines.

LinePlot - Class in smile.plot.swing

Line plot is a special scatter plot which connects points by straight lines.

LinePlot(Line...) - Constructor for class smile.plot.swing.LinePlot

Constructor.

LinePlot(Line[], Legend[]) - Constructor for class smile.plot.swing.LinePlot

Constructor.

link(double) - Method in interface smile.glm.model.Model

The link function.

Linkage - Class in smile.clustering.linkage

A measure of dissimilarity between clusters (i.e.

Linkage(double[][]) - Constructor for class smile.clustering.linkage.Linkage

Constructor.

Linkage(int, float[]) - Constructor for class smile.clustering.linkage.Linkage

Constructor.

ljung(double[], int) - Static method in class smile.timeseries.BoxTest

Box-Pierce test.

Ljung_Box - Enum constant in enum class smile.timeseries.BoxTest.Type

Ljung-Box test.

llama(String) - Static method in interface smile.llm.tokenizer.Tokenizer

Loads a llama3 tokenizer model.

Llama - Class in smile.llm.tokenizer

Custom tokenizer for Llama 3 models.

Llama(Map<Bytes, Integer>) - Constructor for class smile.llm.tokenizer.Llama

Constructor with default BOS, EOS, and special tokens.

Llama(Map<Bytes, Integer>, String, String, String...) - Constructor for class smile.llm.tokenizer.Llama

Constructor.

LLE - Class in smile.manifold

Locally Linear Embedding.

LLE(int[], double[][], AdjacencyList) - Constructor for class smile.manifold.LLE

Constructor.

lloyd(double[][], int) - Static method in class smile.clustering.KMeans

The implementation of Lloyd algorithm as a benchmark.

lloyd(double[][], int, int, double) - Static method in class smile.clustering.KMeans

The implementation of Lloyd algorithm as a benchmark.

LM - Enum constant in enum class smile.math.matrix.ARPACK.AsymmOption

The eigenvalues largest in magnitude.

LM - Enum constant in enum class smile.math.matrix.ARPACK.SymmOption

The eigenvalues largest in magnitude.

LM - Enum constant in enum class smile.math.matrix.fp32.ARPACK.AsymmOption

The eigenvalues largest in magnitude.

LM - Enum constant in enum class smile.math.matrix.fp32.ARPACK.SymmOption

The eigenvalues largest in magnitude.

lo() - Method in class smile.math.kernel.BinarySparseGaussianKernel

lo() - Method in class smile.math.kernel.BinarySparseHyperbolicTangentKernel

lo() - Method in class smile.math.kernel.BinarySparseLaplacianKernel

lo() - Method in class smile.math.kernel.BinarySparseLinearKernel

lo() - Method in class smile.math.kernel.BinarySparseMaternKernel

lo() - Method in class smile.math.kernel.BinarySparsePolynomialKernel

lo() - Method in class smile.math.kernel.BinarySparseThinPlateSplineKernel

lo() - Method in class smile.math.kernel.GaussianKernel

lo() - Method in class smile.math.kernel.HellingerKernel

lo() - Method in class smile.math.kernel.HyperbolicTangentKernel

lo() - Method in class smile.math.kernel.LaplacianKernel

lo() - Method in class smile.math.kernel.LinearKernel

lo() - Method in class smile.math.kernel.MaternKernel

lo() - Method in interface smile.math.kernel.MercerKernel

Returns the lower bound of hyperparameters (in hyperparameter tuning).

lo() - Method in class smile.math.kernel.PearsonKernel

lo() - Method in class smile.math.kernel.PolynomialKernel

lo() - Method in class smile.math.kernel.ProductKernel

lo() - Method in class smile.math.kernel.SparseGaussianKernel

lo() - Method in class smile.math.kernel.SparseHyperbolicTangentKernel

lo() - Method in class smile.math.kernel.SparseLaplacianKernel

lo() - Method in class smile.math.kernel.SparseLinearKernel

lo() - Method in class smile.math.kernel.SparseMaternKernel

lo() - Method in class smile.math.kernel.SparsePolynomialKernel

lo() - Method in class smile.math.kernel.SparseThinPlateSplineKernel

lo() - Method in class smile.math.kernel.SumKernel

lo() - Method in class smile.math.kernel.ThinPlateSplineKernel

load(String) - Method in class smile.deep.Model

Loads a checkpoint.

load(String) - Static method in class smile.llm.tokenizer.Tiktoken

Loads a tiktoken model file.

loadings() - Method in class smile.feature.extraction.PCA

Returns the variable loading matrix, ordered from largest to smallest by corresponding eigenvalues.

loadings() - Method in class smile.feature.extraction.ProbabilisticPCA

Returns the variable loading matrix, ordered from largest to smallest by corresponding eigenvalues.

loess(String, String) - Method in class smile.plot.vega.Transform

Adds a loess transform.

LoessTransform - Class in smile.plot.vega

The loess transform (for locally-estimated scatterplot smoothing) uses locally-estimated regression to produce a trend line.

log() - Static method in interface smile.glm.model.Poisson

log link function.

log(double) - Static method in class smile.math.MathEx

Returns natural log without underflow.

log(String) - Static method in interface smile.data.formula.Terms

The log(x) term.

log(Term) - Static method in interface smile.data.formula.Terms

The log(x) term.

log10(String) - Static method in interface smile.data.formula.Terms

The log10(x) term.

log10(Term) - Static method in interface smile.data.formula.Terms

The log10(x) term.

log1p(String) - Static method in interface smile.data.formula.Terms

The log(1 + x) term.

log1p(Term) - Static method in interface smile.data.formula.Terms

The log(1 + x) term.

log1pe(double) - Static method in class smile.math.MathEx

Returns natural log(1+exp(x)) without overflow.

log2(double) - Static method in class smile.math.MathEx

Log of base 2.

log2(String) - Static method in interface smile.data.formula.Terms

The log2(x) term.

log2(Term) - Static method in interface smile.data.formula.Terms

The log2(x) term.

LogCosh - Class in smile.ica

A good general-purpose contrast function for ICA.

LogCosh() - Constructor for class smile.ica.LogCosh

logdet() - Method in class smile.math.matrix.BandMatrix.Cholesky

Returns the log of matrix determinant.

logdet() - Method in class smile.math.matrix.BigMatrix.Cholesky

Returns the log of matrix determinant.

logdet() - Method in class smile.math.matrix.fp32.BandMatrix.Cholesky

Returns the log of matrix determinant.

logdet() - Method in class smile.math.matrix.fp32.Matrix.Cholesky

Returns the log of matrix determinant.

logdet() - Method in class smile.math.matrix.fp32.SymmMatrix.Cholesky

Returns the log of matrix determinant.

logdet() - Method in class smile.math.matrix.Matrix.Cholesky

Returns the log of matrix determinant.

logdet() - Method in class smile.math.matrix.SymmMatrix.Cholesky

Returns the log of matrix determinant.

logistic(int[]) - Static method in interface smile.base.cart.Loss

Logistic regression loss for binary classification.

logistic(int, int, int[], double[][]) - Static method in interface smile.base.cart.Loss

Logistic regression loss for multi-class classification.

LogisticDistribution - Class in smile.stat.distribution

The logistic distribution is a continuous probability distribution whose cumulative distribution function is the logistic function, which appears in logistic regression and feedforward neural networks.

LogisticDistribution(double, double) - Constructor for class smile.stat.distribution.LogisticDistribution

Constructor.

LogisticRegression - Class in smile.classification

Logistic regression.

LogisticRegression(int, double, double, IntSet) - Constructor for class smile.classification.LogisticRegression

Constructor.

LogisticRegression.Binomial - Class in smile.classification

Binomial logistic regression.

LogisticRegression.Multinomial - Class in smile.classification

Multinomial logistic regression.

logit() - Static method in interface smile.glm.model.Bernoulli

logit link function.

logit(int[]) - Static method in interface smile.glm.model.Binomial

logit link function.

loglikelihood() - Method in class smile.classification.LogisticRegression

Returns the log-likelihood of model.

loglikelihood() - Method in class smile.classification.Maxent

Returns the log-likelihood of model.

loglikelihood() - Method in class smile.classification.SparseLogisticRegression

Returns the log-likelihood of model.

logLikelihood - Variable in class smile.glm.GLM

Log-likelihood.

logLikelihood() - Method in class smile.glm.GLM

Returns the log-likelihood of model.

logLikelihood(double[]) - Method in interface smile.stat.distribution.Distribution

The log likelihood of the sample set following this distribution.

logLikelihood(double[]) - Method in class smile.stat.distribution.KernelDensity

The log likelihood of the samples.

logLikelihood(double[][]) - Method in interface smile.stat.distribution.MultivariateDistribution

The log likelihood of the sample set following this distribution.

logLikelihood(double[], double[]) - Method in interface smile.glm.model.Model

The log-likelihood function.

logLikelihood(int[]) - Method in class smile.stat.distribution.DiscreteDistribution

The likelihood given a sample set following the distribution.

logloss - Variable in class smile.validation.ClassificationMetrics

The log loss on validation data.

LogLoss - Class in smile.validation.metric

Log loss is a evaluation metric for binary classifiers and it is sometimes the optimization objective as well in case of logistic regression and neural networks.

LogLoss() - Constructor for class smile.validation.metric.LogLoss

LogNormalDistribution - Class in smile.stat.distribution

A log-normal distribution is a probability distribution of a random variable whose logarithm is normally distributed.

LogNormalDistribution(double, double) - Constructor for class smile.stat.distribution.LogNormalDistribution

Constructor.

logp(double) - Method in class smile.stat.distribution.BetaDistribution

logp(double) - Method in class smile.stat.distribution.ChiSquareDistribution

logp(double) - Method in class smile.stat.distribution.DiscreteDistribution

logp(double) - Method in interface smile.stat.distribution.Distribution

The density at x in log scale, which may prevents the underflow problem.

logp(double) - Method in class smile.stat.distribution.ExponentialDistribution

logp(double) - Method in class smile.stat.distribution.FDistribution

logp(double) - Method in class smile.stat.distribution.GammaDistribution

logp(double) - Method in class smile.stat.distribution.GaussianDistribution

logp(double) - Method in class smile.stat.distribution.KernelDensity

logp(double) - Method in class smile.stat.distribution.LogisticDistribution

logp(double) - Method in class smile.stat.distribution.LogNormalDistribution

logp(double) - Method in class smile.stat.distribution.Mixture

logp(double) - Method in class smile.stat.distribution.TDistribution

logp(double) - Method in class smile.stat.distribution.WeibullDistribution

logp(double[]) - Method in interface smile.stat.distribution.MultivariateDistribution

The density at x in log scale, which may prevents the underflow problem.

logp(double[]) - Method in class smile.stat.distribution.MultivariateGaussianDistribution

logp(double[]) - Method in class smile.stat.distribution.MultivariateMixture

logp(int) - Method in class smile.stat.distribution.BernoulliDistribution

logp(int) - Method in class smile.stat.distribution.BinomialDistribution

logp(int) - Method in class smile.stat.distribution.DiscreteDistribution

The probability mass function in log scale.

logp(int) - Method in class smile.stat.distribution.DiscreteMixture

logp(int) - Method in class smile.stat.distribution.EmpiricalDistribution

logp(int) - Method in class smile.stat.distribution.GeometricDistribution

logp(int) - Method in class smile.stat.distribution.HyperGeometricDistribution

logp(int) - Method in class smile.stat.distribution.NegativeBinomialDistribution

logp(int) - Method in class smile.stat.distribution.PoissonDistribution

logp(int) - Method in class smile.stat.distribution.ShiftedGeometricDistribution

logp(int[]) - Method in class smile.sequence.HMM

Returns the logarithm probability of an observation sequence given this HMM.

logp(int[], int[]) - Method in class smile.sequence.HMM

Returns the log joint probability of an observation sequence along a state sequence given this HMM.

logp(T[]) - Method in class smile.sequence.HMMLabeler

Returns the logarithm probability of an observation sequence.

logp(T[], int[]) - Method in class smile.sequence.HMMLabeler

Returns the log joint probability of an observation sequence along a state sequence.

logSigmoid(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with log sigmoid activation function.

LogSigmoid - Class in smile.deep.activation

Log sigmoid activation function.

LogSigmoid() - Constructor for class smile.deep.activation.LogSigmoid

Constructor.

logSoftmax(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with log softmax activation function.

LogSoftmax - Class in smile.deep.activation

Log softmax activation function.

LogSoftmax() - Constructor for class smile.deep.activation.LogSoftmax

Constructor.

Long - Enum constant in enum class smile.data.type.DataType.ID

Long type ID.

LONG - Static variable in interface smile.util.Regex

Long regular expression pattern.

LONG_DASH - Enum constant in enum class smile.plot.swing.Line.Style

LongArrayCellRenderer - Class in smile.swing.table

Long array renderer in JTable.

LongArrayCellRenderer() - Constructor for class smile.swing.table.LongArrayCellRenderer

Constructor.

LongArrayType - Static variable in class smile.data.type.DataTypes

Long Array data type.

LongObjectType - Static variable in class smile.data.type.DataTypes

Long Object data type.

LongType - Class in smile.data.type

Long data type.

LongType - Static variable in class smile.data.type.DataTypes

Long data type.

longValue() - Method in class smile.deep.tensor.Tensor

Returns the long value when the tensor holds a single value.

longVector(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

longVector(int) - Method in class smile.data.IndexDataFrame

longVector(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

longVector(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

LongVector - Interface in smile.data.vector

An immutable long vector.

LOOCV - Interface in smile.validation

Leave-one-out cross validation.

lookup(String, String) - Method in class smile.plot.vega.Transform

Adds a lookup transformation.

lookup(String, LookupData) - Method in class smile.plot.vega.Transform

Adds a lookup transformation.

lookupData(String) - Method in class smile.plot.vega.Transform

Creates a lookup data.

LookupData - Class in smile.plot.vega

The density transform performs one-dimensional kernel density estimation over an input data stream and generates a new data stream of samples of the estimated densities.

Loss - Interface in smile.base.cart

Regression loss function.

Loss - Interface in smile.deep

Loss functions.

Loss.Type - Enum Class in smile.base.cart

The type of loss.

lower(int) - Method in class smile.util.PriorityQueue

The value of item k is lower (higher priority) now.

LOWER - Enum constant in enum class smile.math.blas.UPLO

Lower triangle is stored.

lowestCommonAncestor(String, String) - Method in class smile.taxonomy.Taxonomy

Returns the lowest common ancestor (LCA) of concepts v and w.

lowestCommonAncestor(Concept, Concept) - Method in class smile.taxonomy.Taxonomy

Returns the lowest common ancestor (LCA) of concepts v and w.

LR - Enum constant in enum class smile.math.matrix.ARPACK.AsymmOption

The eigenvalues of largest real part.

LR - Enum constant in enum class smile.math.matrix.fp32.ARPACK.AsymmOption

The eigenvalues of largest real part.

ls() - Static method in interface smile.base.cart.Loss

Least squares regression loss.

ls(double[]) - Static method in interface smile.base.cart.Loss

Least squares regression loss.

LS - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

List item marker.

LSH<E> - Class in smile.neighbor

Locality-Sensitive Hashing.

LSH(double[][], E[], double) - Constructor for class smile.neighbor.LSH

Constructor.

LSH(double[][], E[], double, int) - Constructor for class smile.neighbor.LSH

Constructor.

LSH(int, int, int, double) - Constructor for class smile.neighbor.LSH

Constructor.

LSH(int, int, int, double, int) - Constructor for class smile.neighbor.LSH

Constructor.

lt(double) - Method in class smile.deep.tensor.Tensor

Computes element-wise less-than comparison.

lt(int) - Method in class smile.deep.tensor.Tensor

Computes element-wise less-than comparison.

lt(Tensor) - Method in class smile.deep.tensor.Tensor

Computes element-wise less-than comparison.

lu - Variable in class smile.math.matrix.BandMatrix.Cholesky

The Cholesky decomposition.

lu - Variable in class smile.math.matrix.BandMatrix.LU

The LU decomposition.

lu - Variable in class smile.math.matrix.BigMatrix.Cholesky

The Cholesky decomposition.

lu - Variable in class smile.math.matrix.BigMatrix.LU

The LU decomposition.

lu - Variable in class smile.math.matrix.fp32.BandMatrix.Cholesky

The Cholesky decomposition.

lu - Variable in class smile.math.matrix.fp32.BandMatrix.LU

The LU decomposition.

lu - Variable in class smile.math.matrix.fp32.Matrix.Cholesky

The Cholesky decomposition.

lu - Variable in class smile.math.matrix.fp32.Matrix.LU

The LU decomposition.

lu - Variable in class smile.math.matrix.fp32.SymmMatrix.BunchKaufman

The Bunch–Kaufman decomposition.

lu - Variable in class smile.math.matrix.fp32.SymmMatrix.Cholesky

The Cholesky decomposition.

lu - Variable in class smile.math.matrix.Matrix.Cholesky

The Cholesky decomposition.

lu - Variable in class smile.math.matrix.Matrix.LU

The LU decomposition.

lu - Variable in class smile.math.matrix.SymmMatrix.BunchKaufman

The Bunch–Kaufman decomposition.

lu - Variable in class smile.math.matrix.SymmMatrix.Cholesky

The Cholesky decomposition.

lu() - Method in class smile.math.matrix.BandMatrix

LU decomposition.

lu() - Method in class smile.math.matrix.BigMatrix

LU decomposition.

lu() - Method in class smile.math.matrix.fp32.BandMatrix

LU decomposition.

lu() - Method in class smile.math.matrix.fp32.Matrix

LU decomposition.

lu() - Method in class smile.math.matrix.Matrix

LU decomposition.

lu(boolean) - Method in class smile.math.matrix.BigMatrix

LU decomposition.

lu(boolean) - Method in class smile.math.matrix.fp32.Matrix

LU decomposition.

lu(boolean) - Method in class smile.math.matrix.Matrix

LU decomposition.

LU(BandMatrix, int[], int) - Constructor for class smile.math.matrix.BandMatrix.LU

Constructor.

LU(BigMatrix, IntPointer, int) - Constructor for class smile.math.matrix.BigMatrix.LU

Constructor.

LU(BandMatrix, int[], int) - Constructor for class smile.math.matrix.fp32.BandMatrix.LU

Constructor.

LU(Matrix, int[], int) - Constructor for class smile.math.matrix.fp32.Matrix.LU

Constructor.

LU(Matrix, int[], int) - Constructor for class smile.math.matrix.Matrix.LU

Constructor.

M

m - Variable in class smile.math.matrix.BigMatrix.SVD

The number of rows of matrix.

m - Variable in class smile.math.matrix.fp32.Matrix.SVD

The number of rows of matrix.

m - Variable in class smile.math.matrix.Matrix.SVD

The number of rows of matrix.

m - Variable in class smile.neighbor.lsh.PrZ

The index of hash function.

m - Variable in class smile.stat.distribution.HyperGeometricDistribution

The number of defects.

M(double[][], double[]) - Method in interface smile.stat.distribution.MultivariateExponentialFamily

The M step in the EM algorithm, which depends the specific distribution.

M(double[][], double[]) - Method in class smile.stat.distribution.MultivariateGaussianDistribution

M(double[], double[]) - Method in class smile.stat.distribution.BetaDistribution

M(double[], double[]) - Method in class smile.stat.distribution.ChiSquareDistribution

M(double[], double[]) - Method in class smile.stat.distribution.ExponentialDistribution

M(double[], double[]) - Method in interface smile.stat.distribution.ExponentialFamily

The M step in the EM algorithm, which depends on the specific distribution.

M(double[], double[]) - Method in class smile.stat.distribution.GammaDistribution

M(double[], double[]) - Method in class smile.stat.distribution.GaussianDistribution

M(int[], double[]) - Method in interface smile.stat.distribution.DiscreteExponentialFamily

The M step in the EM algorithm, which depends the specific distribution.

M(int[], double[]) - Method in class smile.stat.distribution.GeometricDistribution

M(int[], double[]) - Method in class smile.stat.distribution.PoissonDistribution

M(int[], double[]) - Method in class smile.stat.distribution.ShiftedGeometricDistribution

ma() - Method in class smile.timeseries.ARMA

Returns the linear coefficients of MA(q).

MACHEP - Static variable in class smile.math.MathEx

The largest negative integer such that 1.0 + RADIX^MACHEP ≠ 1.0, except that machep is bounded below by -(DIGITS+3)

Macro - Enum constant in enum class smile.deep.metric.Averaging

Macro-averaging calculates each class's performance metric (e.g., precision, recall) and then takes the arithmetic mean across all classes.

mad - Variable in class smile.validation.RegressionMetrics

The mean absolute deviation on validation data.

mad(double[]) - Static method in class smile.math.MathEx

Returns the median absolute deviation (MAD).

mad(float[]) - Static method in class smile.math.MathEx

Returns the median absolute deviation (MAD).

mad(int[]) - Static method in class smile.math.MathEx

Returns the median absolute deviation (MAD).

MAD - Class in smile.validation.metric

Mean absolute deviation error.

MAD() - Constructor for class smile.validation.metric.MAD

MAGENTA - Static variable in interface smile.plot.swing.Palette

MahalanobisDistance - Class in smile.math.distance

In statistics, Mahalanobis distance is based on correlations between variables by which different patterns can be identified and analyzed.

MahalanobisDistance(double[][]) - Constructor for class smile.math.distance.MahalanobisDistance

Constructor.

main(String[]) - Static method in class smile.nlp.pos.HMMPOSTagger

Train the default model on WSJ and BROWN datasets.

ManhattanDistance - Class in smile.math.distance

Manhattan distance, also known as L₁ distance or L₁ norm, is the sum of the (absolute) differences of their coordinates.

ManhattanDistance() - Constructor for class smile.math.distance.ManhattanDistance

Constructor.

ManhattanDistance(double[]) - Constructor for class smile.math.distance.ManhattanDistance

Constructor.

map(double) - Method in class smile.stat.distribution.Mixture

Returns the index of component with maximum a posteriori probability.

map(double[]) - Method in class smile.stat.distribution.MultivariateMixture

Returns the index of component with maximum a posteriori probability.

map(int) - Method in class smile.stat.distribution.DiscreteMixture

Returns the index of component with maximum a posteriori probability.

marginRanking(Tensor, Tensor, Tensor) - Static method in interface smile.deep.Loss

Margin Ranking Loss Function.

mark(String) - Method in class smile.plot.vega.View

Returns the mark definition object.

Mark - Class in smile.plot.vega

Mark definition object.

market(Path) - Static method in class smile.math.matrix.fp32.IMatrix

Reads a matrix from a Matrix Market File Format file.

market(Path) - Static method in class smile.math.matrix.IMatrix

Reads a matrix from a Matrix Market File Format file.

MARKS - Static variable in class smile.plot.swing.Point

The marks of point.

mask - Variable in class smile.base.mlp.Layer

The dropout mask.

Matern - Class in smile.math.kernel

The class of Matérn kernels is a generalization of the Gaussian/RBF.

Matern(double, double, double, double) - Constructor for class smile.math.kernel.Matern

Constructor.

MaternKernel - Class in smile.math.kernel

The class of Matérn kernels is a generalization of the Gaussian/RBF.

MaternKernel(double, double) - Constructor for class smile.math.kernel.MaternKernel

Constructor.

MaternKernel(double, double, double, double) - Constructor for class smile.math.kernel.MaternKernel

Constructor.

MathEx - Class in smile.math

Extra basic numeric functions.

matmul(Tensor) - Method in class smile.deep.tensor.Tensor

Returns the matrix product of two tensors.

matrix - Variable in class smile.validation.metric.ConfusionMatrix

Confusion matrix.

matrix() - Static method in interface smile.data.DataFrame.Collectors

Returns a stream collector that accumulates tuples into a Matrix.

matrix(DataFrame) - Method in class smile.data.formula.Formula

Returns the design matrix of predictors.

matrix(DataFrame, boolean) - Method in class smile.data.formula.Formula

Returns the design matrix of predictors.

Matrix - Class in smile.math.matrix.fp32

Dense matrix.

Matrix - Class in smile.math.matrix

Dense matrix of double precision values.

Matrix(int, int) - Constructor for class smile.math.matrix.fp32.Matrix

Constructor of zero matrix.

Matrix(int, int) - Constructor for class smile.math.matrix.Matrix

Constructor of zero matrix.

Matrix(int, int, double) - Constructor for class smile.math.matrix.Matrix

Constructor.

Matrix(int, int, float) - Constructor for class smile.math.matrix.fp32.Matrix

Constructor.

Matrix(int, int, int, double[]) - Constructor for class smile.math.matrix.Matrix

Constructor.

Matrix(int, int, int, float[]) - Constructor for class smile.math.matrix.fp32.Matrix

Constructor.

Matrix.Cholesky - Class in smile.math.matrix.fp32

The Cholesky decomposition of a symmetric, positive-definite matrix.

Matrix.Cholesky - Class in smile.math.matrix

The Cholesky decomposition of a symmetric, positive-definite matrix.

Matrix.EVD - Class in smile.math.matrix.fp32

Eigenvalue decomposition.

Matrix.EVD - Class in smile.math.matrix

Eigenvalue decomposition.

Matrix.LU - Class in smile.math.matrix.fp32

The LU decomposition.

Matrix.LU - Class in smile.math.matrix

The LU decomposition.

Matrix.QR - Class in smile.math.matrix.fp32

The QR decomposition.

Matrix.QR - Class in smile.math.matrix

The QR decomposition.

Matrix.SVD - Class in smile.math.matrix.fp32

Singular Value Decomposition.

Matrix.SVD - Class in smile.math.matrix

Singular Value Decomposition.

MatthewsCorrelation - Class in smile.validation.metric

Matthews correlation coefficient.

MatthewsCorrelation() - Constructor for class smile.validation.metric.MatthewsCorrelation

max - Variable in class smile.util.IntSet

The maximum of values.

max(double[]) - Static method in class smile.math.MathEx

Returns the maximum value of an array.

max(double[][]) - Static method in class smile.math.MathEx

Returns the maximum of a matrix.

max(double, double, double) - Static method in class smile.math.MathEx

Returns the maximum of 4 double numbers.

max(double, double, double, double) - Static method in class smile.math.MathEx

Returns the maximum of 4 double numbers.

max(float[]) - Static method in class smile.math.MathEx

Returns the maximum value of an array.

max(float, float, float) - Static method in class smile.math.MathEx

Returns the maximum of 4 float numbers.

max(float, float, float, float) - Static method in class smile.math.MathEx

Returns the maximum of 4 float numbers.

max(int[]) - Static method in class smile.math.MathEx

Returns the maximum value of an array.

max(int[][]) - Static method in class smile.math.MathEx

Returns the maximum of a matrix.

max(int[], int[]) - Static method in class smile.validation.metric.AdjustedMutualInformation

Calculates the adjusted mutual information of (I(y1, y2) - E(MI)) / (max(H(y1), H(y2)) - E(MI)).

max(int[], int[]) - Static method in class smile.validation.metric.NormalizedMutualInformation

Calculates the normalized mutual information of I(y1, y2) / max(H(y1), H(y2)).

max(int, int, int) - Static method in class smile.math.MathEx

Returns the maximum of 3 integer numbers.

max(int, int, int, int) - Static method in class smile.math.MathEx

Returns the maximum of 4 integer numbers.

MAX - Enum constant in enum class smile.validation.metric.AdjustedMutualInformation.Method

I(y1, y2) / max(H(y1), H(y2))

MAX - Enum constant in enum class smile.validation.metric.NormalizedMutualInformation.Method

I(y1, y2) / max(H(y1), H(y2))

MAX - Static variable in class smile.validation.metric.AdjustedMutualInformation

Default instance with max normalization.

MAX - Static variable in class smile.validation.metric.NormalizedMutualInformation

Default instance with max normalization.

MaxAbsScaler - Class in smile.feature.transform

Scales each feature by its maximum absolute value.

MaxAbsScaler() - Constructor for class smile.feature.transform.MaxAbsScaler

maxBins(int) - Method in class smile.plot.vega.BinParams

Sets the maximum number of bins.

maxDepth - Variable in class smile.base.cart.CART

The maximum depth of the tree.

Maxent - Class in smile.classification

Maximum Entropy Classifier.

Maxent(int, double, double, IntSet) - Constructor for class smile.classification.Maxent

Constructor.

Maxent.Binomial - Class in smile.classification

Binomial maximum entropy classifier.

Maxent.Multinomial - Class in smile.classification

Multinomial maximum entropy classifier.

maxExtent(int) - Method in class smile.plot.vega.Axis

Sets the maximum extent in pixels that axis ticks and labels should use.

maxNodes - Variable in class smile.base.cart.CART

The maximum number of leaf nodes in the tree.

maxPool2d(int) - Static method in interface smile.deep.layer.Layer

Returns a max pooling layer that reduces a tensor by combining cells, and assigning the maximum value of the input cells to the output cell.

MaxPool2dLayer - Class in smile.deep.layer

A max pooling layer that reduces a tensor by combining cells, and assigning the maximum value of the input cells to the output cell.

MaxPool2dLayer(int) - Constructor for class smile.deep.layer.MaxPool2dLayer

Constructor.

MaxPool2dLayer(int, int) - Constructor for class smile.deep.layer.MaxPool2dLayer

Constructor.

maxSteps(int) - Method in class smile.plot.vega.DensityTransform

Sets the maximum number of samples to take along the extent domain for plotting the density.

maxtf() - Method in class smile.nlp.SimpleText

maxtf() - Method in interface smile.nlp.TextTerms

Returns the maximum term frequency over all terms in the document.

MBConv - Class in smile.vision.layer

Mobile inverted bottleneck convolution.

MBConv(MBConvConfig, double, IntFunction<Layer>) - Constructor for class smile.vision.layer.MBConv

Constructor.

MBConv(double, int, int, int, int, int) - Static method in record class smile.vision.layer.MBConvConfig

Returns the config for MBConv block.

MBConv(double, int, int, int, int, int, double, double) - Static method in record class smile.vision.layer.MBConvConfig

Returns the config for MBConv block.

MBConvConfig - Record Class in smile.vision.layer

EfficientNet block configuration.

MBConvConfig(double, int, int, int, int, int, String) - Constructor for record class smile.vision.layer.MBConvConfig

Creates an instance of a MBConvConfig record class.

mcc - Variable in class smile.validation.ClassificationMetrics

The Matthews correlation coefficient on validation data.

MD - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Modal verb.

MDS - Class in smile.manifold

Classical multidimensional scaling, also known as principal coordinates analysis.

MDS(double[], double[], double[][]) - Constructor for class smile.manifold.MDS

Constructor.

mean - Variable in class smile.neighbor.lsh.NeighborHashValueModel

The mean of hash values of neighbors.

mean - Variable in class smile.regression.GaussianProcessRegression

The mean of responsible variable.

mean - Variable in class smile.stat.distribution.LogNormalDistribution

The mean.

mean() - Method in class smile.base.cart.RegressionNode

Returns the mean of response variable.

mean() - Method in class smile.deep.tensor.Tensor

Returns the mean of all elements in the tensor.

mean() - Method in class smile.neighbor.lsh.HashValueParzenModel

Returns the mean.

mean() - Method in class smile.stat.distribution.BernoulliDistribution

mean() - Method in class smile.stat.distribution.BetaDistribution

mean() - Method in class smile.stat.distribution.BinomialDistribution

mean() - Method in class smile.stat.distribution.ChiSquareDistribution

mean() - Method in class smile.stat.distribution.DiscreteMixture

mean() - Method in interface smile.stat.distribution.Distribution

Returns the mean of distribution.

mean() - Method in class smile.stat.distribution.EmpiricalDistribution

mean() - Method in class smile.stat.distribution.ExponentialDistribution

mean() - Method in class smile.stat.distribution.FDistribution

mean() - Method in class smile.stat.distribution.GammaDistribution

mean() - Method in class smile.stat.distribution.GaussianDistribution

mean() - Method in class smile.stat.distribution.GeometricDistribution

mean() - Method in class smile.stat.distribution.HyperGeometricDistribution

mean() - Method in class smile.stat.distribution.KernelDensity

mean() - Method in class smile.stat.distribution.LogisticDistribution

mean() - Method in class smile.stat.distribution.LogNormalDistribution

mean() - Method in class smile.stat.distribution.Mixture

mean() - Method in interface smile.stat.distribution.MultivariateDistribution

The mean vector of distribution.

mean() - Method in class smile.stat.distribution.MultivariateGaussianDistribution

mean() - Method in class smile.stat.distribution.MultivariateMixture

mean() - Method in class smile.stat.distribution.NegativeBinomialDistribution

mean() - Method in class smile.stat.distribution.PoissonDistribution

mean() - Method in class smile.stat.distribution.ShiftedGeometricDistribution

mean() - Method in class smile.stat.distribution.TDistribution

mean() - Method in class smile.stat.distribution.WeibullDistribution

mean() - Method in class smile.timeseries.AR

Returns the mean of time series.

mean() - Method in class smile.timeseries.ARMA

Returns the mean of time series.

mean(double[]) - Static method in class smile.math.MathEx

Returns the mean of an array.

mean(float[]) - Static method in class smile.math.MathEx

Returns the mean of an array.

mean(int[]) - Static method in class smile.math.MathEx

Returns the mean of an array.

MEAN_SQUARED_ERROR - Enum constant in enum class smile.base.mlp.Cost

Mean squares error cost.

measure - Variable in class smile.data.type.StructField

Optional levels of measurements.

measure() - Method in interface smile.data.vector.BaseVector

Returns the (optional) level of measurements.

measure(int) - Method in class smile.data.type.StructType

Returns the field's level of measurements.

Measure - Interface in smile.data.measure

Level of measurement or scale of measure is a classification that describes the nature of information within the values assigned to variables.

measures() - Method in interface smile.data.DataFrame

Returns the column's level of measurements.

measures() - Method in interface smile.data.Tuple

Returns the field's level of measurements.

measures() - Method in class smile.data.type.StructType

Returns the field's level of measurements.

MEC<T> - Class in smile.clustering

Non-parametric Minimum Conditional Entropy Clustering.

MEC(double, double, RNNSearch<T, T>, int, int[]) - Constructor for class smile.clustering.MEC

Constructor.

median(double[]) - Static method in class smile.math.MathEx

Find the median of an array of type double.

median(double[]) - Static method in interface smile.sort.QuickSelect

Find the median of an array of type double.

median(float[]) - Static method in class smile.math.MathEx

Find the median of an array of type float.

median(float[]) - Static method in interface smile.sort.QuickSelect

Find the median of an array of type float.

median(int[]) - Static method in class smile.math.MathEx

Find the median of an array of type int.

median(int[]) - Static method in interface smile.sort.QuickSelect

Find the median of an array of type integer.

median(T[]) - Static method in class smile.math.MathEx

Find the median of an array of type double.

median(T[]) - Static method in interface smile.sort.QuickSelect

Find the median of an array of type double.

MercerKernel<T> - Interface in smile.math.kernel

Mercer kernel, also called covariance function in Gaussian process.

merge() - Method in class smile.base.cart.InternalNode

merge() - Method in class smile.base.cart.LeafNode

merge() - Method in interface smile.base.cart.Node

Try to merge the children nodes and return a leaf node.

merge(int, int) - Method in class smile.clustering.linkage.CompleteLinkage

merge(int, int) - Method in class smile.clustering.linkage.Linkage

Merges two clusters into one and update the proximity matrix.

merge(int, int) - Method in class smile.clustering.linkage.SingleLinkage

merge(int, int) - Method in class smile.clustering.linkage.UPGMALinkage

merge(int, int) - Method in class smile.clustering.linkage.UPGMCLinkage

merge(int, int) - Method in class smile.clustering.linkage.WardLinkage

merge(int, int) - Method in class smile.clustering.linkage.WPGMALinkage

merge(int, int) - Method in class smile.clustering.linkage.WPGMCLinkage

merge(RandomForest) - Method in class smile.classification.RandomForest

Merges two random forests.

merge(DataFrame...) - Method in interface smile.data.DataFrame

Merges data frames horizontally by columns.

merge(DataFrame...) - Method in class smile.data.IndexDataFrame

merge(BaseVector...) - Method in interface smile.data.DataFrame

Merges vectors with this data frame.

merge(BaseVector...) - Method in class smile.data.IndexDataFrame

merge(RandomForest) - Method in class smile.regression.RandomForest

Merges two random forests.

MersenneTwister - Class in smile.math.random

32-bit Mersenne Twister.

MersenneTwister() - Constructor for class smile.math.random.MersenneTwister

Constructor.

MersenneTwister(int) - Constructor for class smile.math.random.MersenneTwister

Constructor.

MersenneTwister(long) - Constructor for class smile.math.random.MersenneTwister

Constructor.

MersenneTwister64 - Class in smile.math.random

64-bit Mersenne Twister.

MersenneTwister64() - Constructor for class smile.math.random.MersenneTwister64

Constructor.

MersenneTwister64(long) - Constructor for class smile.math.random.MersenneTwister64

Constructor.

method - Variable in class smile.stat.hypothesis.ChiSqTest

The type of test.

method - Variable in class smile.stat.hypothesis.CorTest

The type of test.

method - Variable in class smile.stat.hypothesis.KSTest

The type of test.

method - Variable in class smile.stat.hypothesis.TTest

The type of test.

method(String) - Method in class smile.plot.vega.ImputeTransform

Sets the imputation method to use for the field value of imputed data objects.

method(String) - Method in class smile.plot.vega.RegressionTransform

Sets the functional form of the regression model.

Metric - Interface in smile.deep.metric

The class metrics keeps track of metric states, which enables them to be able to calculate values through accumulations and synchronizations across multiple processes.

Metric<T> - Interface in smile.math.distance

A metric function defines a distance between elements of a set.

metrics - Variable in class smile.classification.RandomForest.Model

The performance metrics on out-of-bag samples.

metrics - Variable in class smile.regression.RandomForest.Model

The performance metrics on out-of-bag samples.

metrics - Variable in class smile.validation.ClassificationValidation

The classification metrics.

metrics - Variable in class smile.validation.RegressionValidation

The regression metrics.

metrics() - Method in class smile.classification.RandomForest

Returns the overall out-of-bag metric estimations.

metrics() - Method in class smile.regression.RandomForest

Returns the overall out-of-bag metric estimations.

Micro - Enum constant in enum class smile.deep.metric.Averaging

Micro-averaging aggregates the counts of true positives, false positives, and false negatives across all classes and then calculates the performance metric based on the total counts.

MIDNIGHT_BLUE - Static variable in interface smile.plot.swing.Palette

min - Variable in class smile.util.IntSet

The minimum of values.

min(double[]) - Static method in class smile.math.MathEx

Returns the minimum value of an array.

min(double[][]) - Static method in class smile.math.MathEx

Returns the minimum of a matrix.

min(double, double, double) - Static method in class smile.math.MathEx

Returns the minimum of 3 double numbers.

min(double, double, double, double) - Static method in class smile.math.MathEx

Returns the minimum of 4 double numbers.

min(float[]) - Static method in class smile.math.MathEx

Returns the minimum value of an array.

min(float, float, float) - Static method in class smile.math.MathEx

Returns the minimum of 3 float numbers.

min(float, float, float, float) - Static method in class smile.math.MathEx

Returns the minimum of 4 float numbers.

min(int[]) - Static method in class smile.math.MathEx

Returns the minimum value of an array.

min(int[][]) - Static method in class smile.math.MathEx

Returns the minimum of a matrix.

min(int[], int[]) - Static method in class smile.validation.metric.AdjustedMutualInformation

Calculates the adjusted mutual information of (I(y1, y2) - E(MI)) / (min(H(y1), H(y2)) - E(MI)).

min(int[], int[]) - Static method in class smile.validation.metric.NormalizedMutualInformation

Calculates the normalized mutual information of I(y1, y2) / min(H(y1), H(y2)).

min(int, int, int) - Static method in class smile.math.MathEx

Returns the minimum of 3 integer numbers.

min(int, int, int, int) - Static method in class smile.math.MathEx

Returns the minimum of 4 integer numbers.

MIN - Enum constant in enum class smile.validation.metric.AdjustedMutualInformation.Method

I(y1, y2) / min(H(y1), H(y2))

MIN - Enum constant in enum class smile.validation.metric.NormalizedMutualInformation.Method

I(y1, y2) / min(H(y1), H(y2))

MIN - Static variable in class smile.validation.metric.AdjustedMutualInformation

Default instance with min normalization.

MIN - Static variable in class smile.validation.metric.NormalizedMutualInformation

Default instance with min normalization.

minExtent(int) - Method in class smile.plot.vega.Axis

Sets the minimum extent in pixels that axis ticks and labels should use.

minimize(DifferentiableMultivariateFunction, double[], double, int) - Static method in class smile.math.BFGS

This method solves the unconstrained minimization problem

minimize(DifferentiableMultivariateFunction, int, double[], double[], double[], double, int) - Static method in class smile.math.BFGS

This method solves the bound constrained minimization problem using the L-BFGS-B method.

minimize(DifferentiableMultivariateFunction, int, double[], double, int) - Static method in class smile.math.BFGS

This method solves the unconstrained minimization problem

MinkowskiDistance - Class in smile.math.distance

Minkowski distance of order p or L_p-norm, is a generalization of Euclidean distance that is actually L₂-norm.

MinkowskiDistance(int) - Constructor for class smile.math.distance.MinkowskiDistance

Constructor.

MinkowskiDistance(int, double[]) - Constructor for class smile.math.distance.MinkowskiDistance

Constructor.

minmax(double[]) - Static method in class smile.math.Scaler

Returns the scaler that map the values into the range [0, 1].

minPts - Variable in class smile.clustering.DBSCAN

The minimum number of points required to form a cluster

minStep(double) - Method in class smile.plot.vega.BinParams

Sets the minimum allowable step size (particularly useful for integer values).

minSteps(int) - Method in class smile.plot.vega.DensityTransform

Sets the minimum number of samples to take along the extent domain for plotting the density.

minSupport() - Method in class smile.association.FPTree

Returns the required minimum support of item sets in terms of frequency.

MINUTE - Enum constant in enum class smile.data.formula.DateFeature

The minutes represented by an integer from 0 to 59 in the usual manner.

Mixture - Class in smile.stat.distribution

A finite mixture model is a probabilistic model for density estimation using a mixture distribution.

Mixture(Mixture.Component...) - Constructor for class smile.stat.distribution.Mixture

Constructor.

Mixture.Component - Class in smile.stat.distribution

A component in the mixture distribution is defined by a distribution and its weight in the mixture.

mle(int, OutputFunction) - Static method in class smile.base.mlp.Layer

Returns an output layer with (log-)likelihood cost function.

MLP - Class in smile.classification

Fully connected multilayer perceptron neural network for classification.

MLP - Class in smile.regression

Fully connected multilayer perceptron neural network for regression.

MLP(LayerBuilder...) - Constructor for class smile.classification.MLP

Constructor.

MLP(LayerBuilder...) - Constructor for class smile.regression.MLP

Constructor.

MLP(Scaler, LayerBuilder...) - Constructor for class smile.regression.MLP

Constructor.

MLP(IntSet, LayerBuilder...) - Constructor for class smile.classification.MLP

Constructor.

mm(Transpose, BigMatrix, Transpose, BigMatrix) - Method in class smile.math.matrix.BigMatrix

Matrix-matrix multiplication.

mm(Transpose, BigMatrix, Transpose, BigMatrix, double, double) - Method in class smile.math.matrix.BigMatrix

Matrix-matrix multiplication.

mm(Transpose, Matrix, Transpose, Matrix) - Method in class smile.math.matrix.fp32.Matrix

Matrix-matrix multiplication.

mm(Transpose, Matrix, Transpose, Matrix, float, float) - Method in class smile.math.matrix.fp32.Matrix

Matrix-matrix multiplication.

mm(Transpose, Matrix, Transpose, Matrix) - Method in class smile.math.matrix.Matrix

Matrix-matrix multiplication.

mm(Transpose, Matrix, Transpose, Matrix, double, double) - Method in class smile.math.matrix.Matrix

Matrix-matrix multiplication.

mm(BigMatrix) - Method in class smile.math.matrix.BigMatrix

Returns matrix multiplication A * B.

mm(Matrix) - Method in class smile.math.matrix.fp32.Matrix

Returns matrix multiplication A * B.

mm(SparseMatrix) - Method in class smile.math.matrix.fp32.SparseMatrix

Returns the matrix multiplication C = A * B.

mm(Matrix) - Method in class smile.math.matrix.Matrix

Returns matrix multiplication A * B.

mm(SparseMatrix) - Method in class smile.math.matrix.SparseMatrix

Returns the matrix multiplication C = A * B.

MMDDYY - Static variable in class smile.swing.table.DateCellEditor

MMDDYY - Static variable in class smile.swing.table.DateCellRenderer

mnist(String, boolean, int) - Static method in interface smile.deep.Dataset

MNIST contains 70,000 images of handwritten digits: 60,000 for training and 10,000 for testing.

mode(int[]) - Static method in class smile.math.MathEx

Returns the mode of the array, which is the most frequent element.

mode(JSON.Mode) - Method in class smile.io.JSON

Sets the file mode (single-line or multi-line).

model - Variable in class smile.glm.GLM

The model specifications (link function, deviance, etc.).

model - Variable in class smile.sequence.CRFLabeler

The CRF model.

model - Variable in class smile.sequence.HMMLabeler

The HMM model.

model - Variable in class smile.validation.ClassificationValidation

The model.

model - Variable in class smile.validation.RegressionValidation

The model.

Model - Class in smile.deep

The deep learning models.

Model - Interface in smile.glm.model

The GLM model specification.

Model(LayerBlock) - Constructor for class smile.deep.Model

Constructor.

models() - Method in class smile.classification.RandomForest

Returns the base models.

models() - Method in class smile.regression.RandomForest

Returns the base models.

ModelSelection - Interface in smile.validation

Model selection criteria.

momentum - Variable in class smile.base.mlp.MultilayerPerceptron

The momentum factor.

MONTH - Enum constant in enum class smile.data.formula.DateFeature

The month represented by an integer from 1 to 12; 1 is January, 2 is February, and so forth; thus 12 is December.

mouseClicked(MouseEvent) - Method in class smile.swing.table.ButtonCellRenderer

mouseEntered(MouseEvent) - Method in class smile.swing.table.ButtonCellRenderer

mouseExited(MouseEvent) - Method in class smile.swing.table.ButtonCellRenderer

mousePressed(MouseEvent) - Method in class smile.swing.table.ButtonCellRenderer

mouseReleased(MouseEvent) - Method in class smile.swing.table.ButtonCellRenderer

MPLSH<E> - Class in smile.neighbor

Multi-Probe Locality-Sensitive Hashing.

MPLSH(int, int, int, double) - Constructor for class smile.neighbor.MPLSH

Constructor.

MPLSH(int, int, int, double, int) - Constructor for class smile.neighbor.MPLSH

Constructor.

MPS - Enum constant in enum class smile.deep.tensor.DeviceType

GPU for MacOS devices with Metal programming framework.

MPS() - Static method in class smile.deep.tensor.Device

Returns the GPU for MacOS devices with Metal programming framework.

mse - Variable in class smile.validation.RegressionMetrics

The mean squared error on validation data.

mse() - Static method in interface smile.deep.Loss

Mean Squared Error (L2) Loss Function.

mse(int, OutputFunction) - Static method in class smile.base.mlp.Layer

Returns an output layer with mean squared error cost function.

MSE - Class in smile.validation.metric

Mean squared error.

MSE() - Constructor for class smile.validation.metric.MSE

mt(BigMatrix) - Method in class smile.math.matrix.BigMatrix

Returns matrix multiplication A * B'.

mt(Matrix) - Method in class smile.math.matrix.fp32.Matrix

Returns matrix multiplication A * B'.

mt(Matrix) - Method in class smile.math.matrix.Matrix

Returns matrix multiplication A * B'.

mtry - Variable in class smile.base.cart.CART

The number of input variables to be used to determine the decision at a node of the tree.

mu - Variable in class smile.glm.GLM

The fitted mean values.

mu - Variable in class smile.regression.GaussianProcessRegression.JointPrediction

The mean of predictive distribution at query points.

mu - Variable in class smile.stat.distribution.GaussianDistribution

The mean.

mu - Variable in class smile.stat.distribution.LogisticDistribution

The location parameter.

mu - Variable in class smile.stat.distribution.LogNormalDistribution

The mean of normal distribution.

mu - Variable in class smile.stat.distribution.MultivariateGaussianDistribution

The mean vector.

mul(double) - Method in class smile.deep.tensor.Tensor

Returns A * b.

mul(double) - Method in class smile.math.matrix.BigMatrix

A *= b

mul(double) - Method in class smile.math.matrix.Matrix

A *= b

mul(double) - Method in class smile.util.Array2D

A *= x.

mul(float) - Method in class smile.deep.tensor.Tensor

Returns A * b.

mul(float) - Method in class smile.math.matrix.fp32.Matrix

A *= b

mul(int) - Method in class smile.util.IntArray2D

A *= x.

mul(int, int, double) - Method in class smile.math.matrix.BigMatrix

A[i,j] *= b

mul(int, int, double) - Method in class smile.math.matrix.Matrix

A[i,j] *= b

mul(int, int, double) - Method in class smile.util.Array2D

A[i, j] *= x.

mul(int, int, float) - Method in class smile.math.matrix.fp32.Matrix

A[i,j] *= b

mul(int, int, int) - Method in class smile.util.IntArray2D

A[i, j] *= x.

mul(String, String) - Static method in interface smile.data.formula.Terms

Multiplies two terms.

mul(String, Term) - Static method in interface smile.data.formula.Terms

Multiplies two terms.

mul(Term, String) - Static method in interface smile.data.formula.Terms

Multiplies two terms.

mul(Term, Term) - Static method in interface smile.data.formula.Terms

Multiplies two terms.

mul(Tensor) - Method in class smile.deep.tensor.Tensor

Returns A * B element wisely.

mul(Complex) - Method in class smile.math.Complex

Returns this * b.

mul(BigMatrix) - Method in class smile.math.matrix.BigMatrix

Element-wise multiplication A *= B

mul(Matrix) - Method in class smile.math.matrix.fp32.Matrix

Element-wise multiplication A *= B

mul(Matrix) - Method in class smile.math.matrix.Matrix

Element-wise multiplication A *= B

mul(Array2D) - Method in class smile.util.Array2D

A *= B.

mul(IntArray2D) - Method in class smile.util.IntArray2D

A *= B.

Mul - Class in smile.data.formula

The term of a * b expression.

Mul(Term, Term) - Constructor for class smile.data.formula.Mul

Constructor.

mul_(double) - Method in class smile.deep.tensor.Tensor

Returns A *= b.

mul_(float) - Method in class smile.deep.tensor.Tensor

Returns A *= b.

mul_(Tensor) - Method in class smile.deep.tensor.Tensor

Returns A *= B element wisely.

MULTI_LINE - Enum constant in enum class smile.io.JSON.Mode

A JSON object may occupy multiple lines.

MultiColumnSortTableHeaderCellRenderer - Class in smile.swing.table

An extension of DefaultTableHeaderCellRenderer that paints sort icons on the header of each sorted column with varying opacity.

MultiColumnSortTableHeaderCellRenderer() - Constructor for class smile.swing.table.MultiColumnSortTableHeaderCellRenderer

Constructs a MultisortTableHeaderCellRenderer with a default alpha of 0.5.

MultiColumnSortTableHeaderCellRenderer(float) - Constructor for class smile.swing.table.MultiColumnSortTableHeaderCellRenderer

Constructs a MultisortTableHeaderCellRenderer with the specified alpha.

MultilayerPerceptron - Class in smile.base.mlp

Fully connected multilayer perceptron neural network.

MultilayerPerceptron(Layer...) - Constructor for class smile.base.mlp.MultilayerPerceptron

Constructor.

multinomial(double[][], int[]) - Static method in class smile.classification.LogisticRegression

Fits multinomial logistic regression.

multinomial(double[][], int[], double, double, int) - Static method in class smile.classification.LogisticRegression

Fits multinomial logistic regression.

multinomial(double[][], int[], Properties) - Static method in class smile.classification.LogisticRegression

Fits multinomial logistic regression.

multinomial(int, int[][], int[]) - Static method in class smile.classification.Maxent

Fits maximum entropy classifier.

multinomial(int, int[][], int[], double, double, int) - Static method in class smile.classification.Maxent

Fits maximum entropy classifier.

multinomial(int, int[][], int[], Properties) - Static method in class smile.classification.Maxent

Fits maximum entropy classifier.

multinomial(SparseDataset<Integer>) - Static method in class smile.classification.SparseLogisticRegression

Fits multinomial logistic regression.

multinomial(SparseDataset<Integer>, double, double, int) - Static method in class smile.classification.SparseLogisticRegression

Fits multinomial logistic regression.

multinomial(SparseDataset<Integer>, Properties) - Static method in class smile.classification.SparseLogisticRegression

Fits multinomial logistic regression.

Multinomial(double[][], double, double, IntSet) - Constructor for class smile.classification.LogisticRegression.Multinomial

Constructor.

Multinomial(double[][], double, double, IntSet) - Constructor for class smile.classification.Maxent.Multinomial

Constructor.

Multinomial(double[][], double, double, IntSet) - Constructor for class smile.classification.SparseLogisticRegression.Multinomial

Constructor.

MULTINOMIAL - Enum constant in enum class smile.classification.DiscreteNaiveBayes.Model

The document multinomial model generates one term from the vocabulary in each position of the document.

MultiProbeHash - Class in smile.neighbor.lsh

The hash function for data in Euclidean spaces.

MultiProbeHash(int, int, double, int) - Constructor for class smile.neighbor.lsh.MultiProbeHash

Constructor.

MultiProbeSample - Class in smile.neighbor.lsh

Training sample for MPLSH.

MultiProbeSample(double[], List<double[]>) - Constructor for class smile.neighbor.lsh.MultiProbeSample

Constructor.

MultiquadricRadialBasis - Class in smile.math.rbf

Multiquadric RBF.

MultiquadricRadialBasis() - Constructor for class smile.math.rbf.MultiquadricRadialBasis

Constructor.

MultiquadricRadialBasis(double) - Constructor for class smile.math.rbf.MultiquadricRadialBasis

Constructor.

MultivariateDistribution - Interface in smile.stat.distribution

Probability distribution of multivariate random variable.

MultivariateExponentialFamily - Interface in smile.stat.distribution

The purpose of this interface is mainly to define the method M that is the Maximization step in the EM algorithm.

MultivariateExponentialFamilyMixture - Class in smile.stat.distribution

The finite mixture of distributions from multivariate exponential family.

MultivariateExponentialFamilyMixture(MultivariateMixture.Component...) - Constructor for class smile.stat.distribution.MultivariateExponentialFamilyMixture

Constructor.

MultivariateFunction - Interface in smile.math

An interface representing a multivariate real function.

MultivariateGaussianDistribution - Class in smile.stat.distribution

Multivariate Gaussian distribution.

MultivariateGaussianDistribution(double[], double) - Constructor for class smile.stat.distribution.MultivariateGaussianDistribution

Constructor.

MultivariateGaussianDistribution(double[], double[]) - Constructor for class smile.stat.distribution.MultivariateGaussianDistribution

Constructor.

MultivariateGaussianDistribution(double[], Matrix) - Constructor for class smile.stat.distribution.MultivariateGaussianDistribution

Constructor.

MultivariateGaussianMixture - Class in smile.stat.distribution

Finite multivariate Gaussian mixture.

MultivariateGaussianMixture(MultivariateMixture.Component...) - Constructor for class smile.stat.distribution.MultivariateGaussianMixture

Constructor.

MultivariateMixture - Class in smile.stat.distribution

The finite mixture of multivariate distributions.

MultivariateMixture(MultivariateMixture.Component...) - Constructor for class smile.stat.distribution.MultivariateMixture

Constructor.

MultivariateMixture.Component - Class in smile.stat.distribution

A component in the mixture distribution is defined by a distribution and its weight in the mixture.

MurmurHash2 - Interface in smile.hash

MurmurHash is a very fast, non-cryptographic hash suitable for general hash-based lookup.

MurmurHash3 - Class in smile.hash

MurmurHash is a very fast, non-cryptographic hash suitable for general hash-based lookup.

MurmurHash3() - Constructor for class smile.hash.MurmurHash3

mustart(double) - Method in interface smile.glm.model.Model

The function to estimates the starting value of mean given y.

MutableInt - Class in smile.util

A mutable int wrapper.

MutableInt() - Constructor for class smile.util.MutableInt

Constructor.

MutableInt(int) - Constructor for class smile.util.MutableInt

Constructor.

MutableLSH<E> - Class in smile.neighbor

Mutable LSH.

MutableLSH(int, int, int, double) - Constructor for class smile.neighbor.MutableLSH

Constructor.

mutate() - Method in class smile.gap.BitString

mutate() - Method in interface smile.gap.Chromosome

For genetic algorithms, this method mutates the chromosome randomly.

MutualInformation - Class in smile.validation.metric

Mutual Information for comparing clustering.

MutualInformation() - Constructor for class smile.validation.metric.MutualInformation

mv(double[]) - Method in class smile.math.matrix.IMatrix

Returns the matrix-vector multiplication A * x.

mv(double[], double[]) - Method in class smile.math.matrix.IMatrix

Matrix-vector multiplication y = A * x.

mv(double[], int, int) - Method in class smile.math.matrix.BandMatrix

mv(double[], int, int) - Method in class smile.math.matrix.BigMatrix

mv(double[], int, int) - Method in class smile.math.matrix.IMatrix

Matrix-vector multiplication A * x.

mv(double[], int, int) - Method in class smile.math.matrix.Matrix

mv(double[], int, int) - Method in class smile.math.matrix.SparseMatrix

mv(double[], int, int) - Method in class smile.math.matrix.SymmMatrix

mv(double, double[], double, double[]) - Method in class smile.math.matrix.IMatrix

Matrix-vector multiplication.

mv(float[]) - Method in class smile.math.matrix.fp32.IMatrix

Returns the matrix-vector multiplication A * x.

mv(float[], float[]) - Method in class smile.math.matrix.fp32.IMatrix

Matrix-vector multiplication y = A * x.

mv(float[], int, int) - Method in class smile.math.matrix.fp32.BandMatrix

mv(float[], int, int) - Method in class smile.math.matrix.fp32.IMatrix

Matrix-vector multiplication A * x.

mv(float[], int, int) - Method in class smile.math.matrix.fp32.Matrix

mv(float[], int, int) - Method in class smile.math.matrix.fp32.SparseMatrix

mv(float[], int, int) - Method in class smile.math.matrix.fp32.SymmMatrix

mv(float, float[], float, float[]) - Method in class smile.math.matrix.fp32.IMatrix

Matrix-vector multiplication.

mv(Transpose, double, double[], double, double[]) - Method in class smile.math.matrix.BandMatrix

mv(Transpose, double, double[], double, double[]) - Method in class smile.math.matrix.BigMatrix

mv(Transpose, double, double[], double, double[]) - Method in class smile.math.matrix.IMatrix

Matrix-vector multiplication.

mv(Transpose, double, double[], double, double[]) - Method in class smile.math.matrix.Matrix

mv(Transpose, double, double[], double, double[]) - Method in class smile.math.matrix.SparseMatrix

mv(Transpose, double, double[], double, double[]) - Method in class smile.math.matrix.SymmMatrix

mv(Transpose, float, float[], float, float[]) - Method in class smile.math.matrix.fp32.BandMatrix

mv(Transpose, float, float[], float, float[]) - Method in class smile.math.matrix.fp32.IMatrix

Matrix-vector multiplication.

mv(Transpose, float, float[], float, float[]) - Method in class smile.math.matrix.fp32.Matrix

mv(Transpose, float, float[], float, float[]) - Method in class smile.math.matrix.fp32.SparseMatrix

mv(Transpose, float, float[], float, float[]) - Method in class smile.math.matrix.fp32.SymmMatrix

MYSQL - Enum constant in enum class smile.nlp.dictionary.EnglishStopWords

The stop words list used by MySQL FullText feature.

N

n - Variable in class smile.base.mlp.Layer

The number of neurons in this layer

n - Variable in class smile.math.matrix.BigMatrix.SVD

The number of columns of matrix.

n - Variable in class smile.math.matrix.fp32.Matrix.SVD

The number of columns of matrix.

n - Variable in class smile.math.matrix.Matrix.SVD

The number of columns of matrix.

n - Variable in class smile.stat.distribution.BinomialDistribution

The number of experiments.

n - Variable in class smile.stat.distribution.HyperGeometricDistribution

The number of draws.

n - Variable in class smile.validation.metric.ContingencyTable

The number of observations.

N - Variable in class smile.stat.distribution.HyperGeometricDistribution

The number of total samples.

n1 - Variable in class smile.validation.metric.ContingencyTable

The number of clusters of first clustering.

n2 - Variable in class smile.validation.metric.ContingencyTable

The number of clusters of second clustering.

NaiveBayes - Class in smile.classification

Naive Bayes classifier.

NaiveBayes(double[], Distribution[][]) - Constructor for class smile.classification.NaiveBayes

Constructor of general naive Bayes classifier.

NaiveBayes(double[], Distribution[][], IntSet) - Constructor for class smile.classification.NaiveBayes

Constructor of general naive Bayes classifier.

name - Variable in class smile.data.type.StructField

Field name.

name() - Method in interface smile.base.mlp.activation.ActivationFunction

Returns the name of activation function.

name() - Method in class smile.base.mlp.activation.LeakyReLU

name() - Method in class smile.base.mlp.activation.ReLU

name() - Method in class smile.base.mlp.activation.Sigmoid

name() - Method in class smile.base.mlp.activation.Softmax

name() - Method in class smile.base.mlp.activation.Tanh

name() - Method in interface smile.base.mlp.ActivationFunction

Returns the name of activation function.

name() - Method in class smile.data.type.ArrayType

name() - Method in class smile.data.type.BooleanType

name() - Method in class smile.data.type.ByteType

name() - Method in class smile.data.type.CharType

name() - Method in interface smile.data.type.DataType

Returns the type name used in external catalogs.

name() - Method in class smile.data.type.DateTimeType

name() - Method in class smile.data.type.DateType

name() - Method in class smile.data.type.DecimalType

name() - Method in class smile.data.type.DoubleType

name() - Method in class smile.data.type.FloatType

name() - Method in class smile.data.type.IntegerType

name() - Method in class smile.data.type.LongType

name() - Method in class smile.data.type.ObjectType

name() - Method in class smile.data.type.ShortType

name() - Method in class smile.data.type.StringType

name() - Method in class smile.data.type.StructType

name() - Method in class smile.data.type.TimeType

name() - Method in interface smile.data.vector.BaseVector

Returns the (optional) name of vector.

name() - Method in class smile.deep.activation.ActivationFunction

Returns the name of activation function.

name() - Method in class smile.deep.metric.Accuracy

name() - Method in interface smile.deep.metric.Metric

Returns the name of metric.

name() - Method in class smile.deep.metric.Precision

name() - Method in class smile.deep.metric.Recall

name() - Method in class smile.io.Arff

Returns the name of relation.

name(int) - Method in class smile.data.type.StructType

Returns the field name.

name(String) - Method in class smile.plot.vega.Concat

name(String) - Method in class smile.plot.vega.Data

Sets a placeholder name and bind data at runtime.

name(String) - Method in class smile.plot.vega.Facet

name(String) - Method in class smile.plot.vega.Repeat

name(String) - Method in class smile.plot.vega.VegaLite

Sets the name of the visualization for later reference.

name(String) - Method in class smile.plot.vega.View

names() - Method in interface smile.data.DataFrame

Returns the column names.

names() - Method in interface smile.data.Tuple

Returns the field names.

names() - Method in class smile.data.type.StructType

Returns the field names.

NAVY_BLUE - Static variable in interface smile.plot.swing.Palette

nbigram() - Method in interface smile.nlp.Corpus

Returns the number of bigrams in the corpus.

nbigram() - Method in class smile.nlp.SimpleCorpus

ncol() - Method in interface smile.data.BinarySparseDataset

Returns the number of columns.

ncol() - Method in interface smile.data.DataFrame

Returns the number of columns.

ncol() - Method in class smile.data.IndexDataFrame

ncol() - Method in interface smile.data.SparseDataset

Returns the number of columns.

ncol() - Method in class smile.math.matrix.BandMatrix

ncol() - Method in class smile.math.matrix.BigMatrix

ncol() - Method in class smile.math.matrix.fp32.BandMatrix

ncol() - Method in class smile.math.matrix.fp32.IMatrix

Returns the number of columns.

ncol() - Method in class smile.math.matrix.fp32.Matrix

ncol() - Method in class smile.math.matrix.fp32.SparseMatrix

ncol() - Method in class smile.math.matrix.fp32.SymmMatrix

ncol() - Method in class smile.math.matrix.IMatrix

Returns the number of columns.

ncol() - Method in class smile.math.matrix.Matrix

ncol() - Method in class smile.math.matrix.SparseMatrix

ncol() - Method in class smile.math.matrix.SymmMatrix

ncol() - Method in class smile.util.Array2D

Returns the number of columns.

ncol() - Method in class smile.util.IntArray2D

Returns the number of columns.

ndoc() - Method in interface smile.nlp.Corpus

Returns the number of documents in the corpus.

ndoc() - Method in class smile.nlp.SimpleCorpus

ne(double) - Method in class smile.deep.tensor.Tensor

Computes element-wise inequality.

ne(int) - Method in class smile.deep.tensor.Tensor

Computes element-wise inequality.

ne(Tensor) - Method in class smile.deep.tensor.Tensor

Computes element-wise inequality.

nearest(double[]) - Method in class smile.neighbor.KDTree

nearest(double[]) - Method in class smile.neighbor.LSH

nearest(double[]) - Method in class smile.neighbor.MPLSH

nearest(double[], double, int) - Method in class smile.neighbor.MPLSH

Returns the approximate nearest neighbor.

nearest(K) - Method in interface smile.neighbor.KNNSearch

Returns the nearest neighbor.

nearest(K) - Method in class smile.neighbor.LinearSearch

NegativeBinomialDistribution - Class in smile.stat.distribution

Negative binomial distribution arises as the probability distribution of the number of successes in a series of independent and identically distributed Bernoulli trials needed to get a specified (non-random) number r of failures.

NegativeBinomialDistribution(double, double) - Constructor for class smile.stat.distribution.NegativeBinomialDistribution

Constructor.

NEGEP - Static variable in class smile.math.MathEx

The largest negative integer such that 1.0 - RADIX^NEGEP ≠ 1.0, except that negeps is bounded below by -(DIGITS+3)

neighbor - Variable in class smile.vq.hebb.Edge

The neighbor neuron.

Neighbor<K,V> - Class in smile.neighbor

The immutable object encapsulates the results of nearest neighbor search.

Neighbor(K, V, int, double) - Constructor for class smile.neighbor.Neighbor

Constructor.

NeighborHashValueModel - Class in smile.neighbor.lsh

Gaussian model of hash values of nearest neighbor.

NeighborHashValueModel(double[], double[], double[]) - Constructor for class smile.neighbor.lsh.NeighborHashValueModel

Constructor.

Neighborhood - Interface in smile.vq

The neighborhood function for 2-dimensional lattice topology (e.g.

neighbors - Variable in class smile.neighbor.lsh.MultiProbeSample

The neighbors of query object in terms of kNN or range search.

net - Variable in class smile.base.mlp.MultilayerPerceptron

The input and hidden layers.

network() - Method in class smile.vq.NeuralGas

Returns the network of neurons.

NeuralGas - Class in smile.vq

Neural Gas soft competitive learning algorithm.

NeuralGas(double[][], TimeFunction, TimeFunction, TimeFunction) - Constructor for class smile.vq.NeuralGas

Constructor.

NeuralMap - Class in smile.vq

NeuralMap is an efficient competitive learning algorithm inspired by growing neural gas and BIRCH.

NeuralMap(double, double, double, int, double) - Constructor for class smile.vq.NeuralMap

Constructor.

Neuron - Class in smile.vq.hebb

The neuron vertex in the growing neural gas network.

Neuron(double[]) - Constructor for class smile.vq.hebb.Neuron

Constructor.

Neuron(double[], double) - Constructor for class smile.vq.hebb.Neuron

Constructor.

neurons - Variable in class smile.base.mlp.LayerBuilder

The number of neurons.

neurons() - Method in class smile.base.mlp.LayerBuilder

Returns the number of neurons.

neurons() - Method in class smile.vq.GrowingNeuralGas

Returns the neurons in the network.

neurons() - Method in class smile.vq.NeuralGas

Returns the neurons.

neurons() - Method in class smile.vq.NeuralMap

Returns the neurons.

neurons() - Method in class smile.vq.SOM

Returns the lattice of neurons.

newInstance() - Method in class smile.gap.BitString

newInstance() - Method in interface smile.gap.Chromosome

Returns a new random instance.

newInstance(byte[]) - Method in class smile.gap.BitString

Creates a new instance with given bits.

newNode(int[]) - Method in class smile.base.cart.CART

Creates a new leaf node.

newNode(int[]) - Method in class smile.classification.DecisionTree

newNode(int[]) - Method in class smile.regression.RegressionTree

newOnes(long...) - Method in class smile.deep.tensor.Tensor

Returns a tensor filled with all ones.

newZeros(long...) - Method in class smile.deep.tensor.Tensor

Returns a tensor filled with all zeros.

next(int) - Method in class smile.math.random.MersenneTwister

next(int) - Method in class smile.math.random.MersenneTwister64

next(int) - Method in interface smile.math.random.RandomNumberGenerator

Returns up to 32 random bits.

next(int) - Method in class smile.math.random.UniversalGenerator

nextDouble() - Method in class smile.math.random.MersenneTwister

nextDouble() - Method in class smile.math.random.MersenneTwister64

nextDouble() - Method in class smile.math.Random

Generator a random number uniformly distributed in [0, 1).

nextDouble() - Method in interface smile.math.random.RandomNumberGenerator

Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence.

nextDouble() - Method in class smile.math.random.UniversalGenerator

nextDouble(double, double) - Method in class smile.math.Random

Generate a uniform random number in the range [lo, hi)

nextDoubles(double[]) - Method in class smile.math.random.MersenneTwister

nextDoubles(double[]) - Method in class smile.math.random.MersenneTwister64

nextDoubles(double[]) - Method in class smile.math.Random

Generate n uniform random numbers in the range [0, 1)

nextDoubles(double[]) - Method in interface smile.math.random.RandomNumberGenerator

Returns a vector of pseudorandom, uniformly distributed double values between 0.0 and 1.0 from this random number generator's sequence.

nextDoubles(double[]) - Method in class smile.math.random.UniversalGenerator

nextDoubles(double[], double, double) - Method in class smile.math.Random

Generate n uniform random numbers in the range [lo, hi)

nextInt() - Method in class smile.math.random.MersenneTwister

nextInt() - Method in class smile.math.random.MersenneTwister64

nextInt() - Method in class smile.math.Random

Returns a random integer.

nextInt() - Method in interface smile.math.random.RandomNumberGenerator

Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence.

nextInt() - Method in class smile.math.random.UniversalGenerator

nextInt(int) - Method in class smile.math.random.MersenneTwister

nextInt(int) - Method in class smile.math.random.MersenneTwister64

nextInt(int) - Method in class smile.math.Random

Returns a random integer in [0, n).

nextInt(int) - Method in interface smile.math.random.RandomNumberGenerator

Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.

nextInt(int) - Method in class smile.math.random.UniversalGenerator

nextLong() - Method in class smile.math.random.MersenneTwister

nextLong() - Method in class smile.math.random.MersenneTwister64

nextLong() - Method in class smile.math.Random

Returns a random long integer.

nextLong() - Method in interface smile.math.random.RandomNumberGenerator

Returns the next pseudorandom, uniformly distributed long value from this random number generator's sequence.

nextLong() - Method in class smile.math.random.UniversalGenerator

NGram - Class in smile.nlp.collocation

An n-gram is a contiguous sequence of n words from a given sequence of text.

NGram - Class in smile.nlp

An n-gram is a contiguous sequence of n words from a given sequence of text.

NGram(String[]) - Constructor for class smile.nlp.NGram

Constructor.

NGram(String[], int) - Constructor for class smile.nlp.collocation.NGram

Constructor.

ni - Variable in class smile.classification.ClassLabels

The number of samples per classes.

nice(int) - Method in class smile.plot.vega.BinParams

If true, attempts to make the bin boundaries use human-friendly boundaries, such as multiples of ten.

nll() - Static method in interface smile.deep.Loss

Negative Log-Likelihood Loss Function.

NN - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Noun, singular or mass.

NNP - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Proper noun, singular.

NNPS - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Proper noun, plural.

NNS - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Noun, plural.

NO_TRANSPOSE - Enum constant in enum class smile.math.blas.Transpose

Normal operation on the matrix.

NO_VECTORS - Enum constant in enum class smile.math.blas.EVDJob

Eigenvalues only are computed.

NO_VECTORS - Enum constant in enum class smile.math.blas.SVDJob

No singular vectors are computed.

Node - Interface in smile.base.cart

CART tree node.

Node(K) - Constructor for class smile.nlp.Trie.Node

Constructor.

nodeSize - Variable in class smile.base.cart.CART

The number of instances in a node below which the tree will not split, setting nodeSize = 5 generally gives good results.

noGradGuard() - Static method in class smile.deep.tensor.Tensor

Disables gradient calculation.

noise - Variable in class smile.regression.GaussianProcessRegression

The variance of noise.

nominal() - Method in interface smile.data.vector.StringVector

Returns a nominal scale of measure based on distinct values in the vector.

NominalNode - Class in smile.base.cart

A node with a nominal split variable.

NominalNode(int, int, double, double, Node, Node) - Constructor for class smile.base.cart.NominalNode

Constructor.

NominalScale - Class in smile.data.measure

Nominal variables take on a limited number of unordered values.

NominalScale(int[], String[]) - Constructor for class smile.data.measure.NominalScale

Constructor.

NominalScale(Class<? extends Enum>) - Constructor for class smile.data.measure.NominalScale

Constructor.

NominalScale(String...) - Constructor for class smile.data.measure.NominalScale

Constructor.

NominalScale(List<String>) - Constructor for class smile.data.measure.NominalScale

Constructor.

NominalSplit - Class in smile.base.cart

The data about of a potential split for a leaf node.

NominalSplit(LeafNode, int, int, double, int, int, int, int, IntPredicate) - Constructor for class smile.base.cart.NominalSplit

Constructor.

NON_UNIT - Enum constant in enum class smile.math.blas.Diag

Non-unit triangular.

None - Static variable in class smile.deep.tensor.Index

The None is used to insert a singleton dimension ("unsqueeze" a dimension).

nonoverlap(int[], int) - Static method in interface smile.validation.CrossValidation

Cross validation with non-overlapping groups.

nonzeros() - Method in class smile.math.matrix.fp32.SparseMatrix

Returns the stream of the non-zero elements.

nonzeros() - Method in class smile.math.matrix.SparseMatrix

Returns the stream of the non-zero elements.

nonzeros(int, int) - Method in class smile.math.matrix.fp32.SparseMatrix

Returns the stream of the non-zero elements in given column range.

nonzeros(int, int) - Method in class smile.math.matrix.SparseMatrix

Returns the stream of the non-zero elements in given column range.

norm() - Method in class smile.math.matrix.BigMatrix

L₂ matrix norm that is the maximum singular value.

norm() - Method in class smile.math.matrix.BigMatrix.SVD

Returns the L₂ matrix norm that is the largest singular value.

norm() - Method in class smile.math.matrix.fp32.Matrix

L₂ matrix norm that is the maximum singular value.

norm() - Method in class smile.math.matrix.fp32.Matrix.SVD

Returns the L₂ matrix norm that is the largest singular value.

norm() - Method in class smile.math.matrix.Matrix

L₂ matrix norm that is the maximum singular value.

norm() - Method in class smile.math.matrix.Matrix.SVD

Returns the L₂ matrix norm that is the largest singular value.

norm(double[]) - Static method in class smile.math.MathEx

L₂ vector norm.

norm(float[]) - Static method in class smile.math.MathEx

L₂ vector norm.

norm1() - Method in class smile.math.matrix.BigMatrix

L₁ matrix norm that is the maximum of column sums.

norm1() - Method in class smile.math.matrix.fp32.Matrix

L₁ matrix norm that is the maximum of column sums.

norm1() - Method in class smile.math.matrix.Matrix

L₁ matrix norm that is the maximum of column sums.

norm1(double[]) - Static method in class smile.math.MathEx

L₁ vector norm.

norm1(float[]) - Static method in class smile.math.MathEx

L₁ vector norm.

norm2() - Method in class smile.math.matrix.BigMatrix

L₂ matrix norm that is the maximum singular value.

norm2() - Method in class smile.math.matrix.fp32.Matrix

L₂ matrix norm that is the maximum singular value.

norm2() - Method in class smile.math.matrix.Matrix

L₂ matrix norm that is the maximum singular value.

norm2(double[]) - Static method in class smile.math.MathEx

L₂ vector norm.

norm2(float[]) - Static method in class smile.math.MathEx

L₂ vector norm.

normalize(double[][]) - Static method in class smile.math.MathEx

Unitizes each column of a matrix to unit length (L_2 norm).

normalize(double[][], boolean) - Static method in class smile.math.MathEx

Unitizes each column of a matrix to unit length (L_2 norm).

normalize(String) - Method in interface smile.nlp.normalizer.Normalizer

Normalize the given string.

normalize(String) - Method in class smile.nlp.normalizer.SimpleNormalizer

NormalizedMutualInformation - Class in smile.validation.metric

Normalized Mutual Information (NMI) for comparing clustering.

NormalizedMutualInformation(NormalizedMutualInformation.Method) - Constructor for class smile.validation.metric.NormalizedMutualInformation

Constructor.

NormalizedMutualInformation.Method - Enum Class in smile.validation.metric

The normalization method.

normalizedNumberFormat(String) - Method in class smile.plot.vega.FormatConfig

Sets custom normalized number format.

normalizedNumberFormatType(String) - Method in class smile.plot.vega.FormatConfig

Sets custom normalized number format type.

Normalizer - Class in smile.feature.transform

Normalize samples individually to unit norm.

Normalizer - Interface in smile.nlp.normalizer

Normalization transforms text into a canonical form by removing unwanted variations.

Normalizer(Normalizer.Norm, String...) - Constructor for class smile.feature.transform.Normalizer

Constructor.

Normalizer.Norm - Enum Class in smile.feature.transform

Vector norm.

normFro() - Method in class smile.math.matrix.BigMatrix

Frobenius matrix norm that is the square root of sum of squares of all elements.

normFro() - Method in class smile.math.matrix.fp32.Matrix

Frobenius matrix norm that is the square root of sum of squares of all elements.

normFro() - Method in class smile.math.matrix.Matrix

Frobenius matrix norm that is the square root of sum of squares of all elements.

normInf() - Method in class smile.math.matrix.BigMatrix

L_∞ matrix norm that is the maximum of row sums.

normInf() - Method in class smile.math.matrix.fp32.Matrix

L_∞ matrix norm that is the maximum of row sums.

normInf() - Method in class smile.math.matrix.Matrix

L_∞ matrix norm that is the maximum of row sums.

normInf(double[]) - Static method in class smile.math.MathEx

L_∞ vector norm.

normInf(float[]) - Static method in class smile.math.MathEx

L_∞ vector norm that is the maximum absolute value.

normLayer() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns the value of the normLayer record component.

not(Predicate) - Static method in class smile.plot.vega.Predicate

Logical NOT operation.

nrm2(double[]) - Method in interface smile.math.blas.BLAS

Computes the Euclidean (L2) norm of a vector.

nrm2(float[]) - Method in interface smile.math.blas.BLAS

Computes the Euclidean (L2) norm of a vector.

nrm2(int, double[], int) - Method in interface smile.math.blas.BLAS

Computes the Euclidean (L2) norm of a vector.

nrm2(int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

nrm2(int, float[], int) - Method in interface smile.math.blas.BLAS

Computes the Euclidean (L2) norm of a vector.

nrm2(int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

nrow() - Method in interface smile.data.DataFrame

Returns the number of rows.

nrow() - Method in interface smile.data.SparseDataset

Returns the number of rows.

nrow() - Method in class smile.math.matrix.BandMatrix

nrow() - Method in class smile.math.matrix.BigMatrix

nrow() - Method in class smile.math.matrix.fp32.BandMatrix

nrow() - Method in class smile.math.matrix.fp32.IMatrix

Returns the number of rows.

nrow() - Method in class smile.math.matrix.fp32.Matrix

nrow() - Method in class smile.math.matrix.fp32.SparseMatrix

nrow() - Method in class smile.math.matrix.fp32.SymmMatrix

nrow() - Method in class smile.math.matrix.IMatrix

Returns the number of rows.

nrow() - Method in class smile.math.matrix.Matrix

nrow() - Method in class smile.math.matrix.SparseMatrix

nrow() - Method in class smile.math.matrix.SymmMatrix

nrow() - Method in class smile.util.Array2D

Returns the number of rows.

nrow() - Method in class smile.util.IntArray2D

Returns the number of rows.

nterm() - Method in interface smile.nlp.Corpus

Returns the number of unique terms in the corpus.

nterm() - Method in class smile.nlp.SimpleCorpus

nu - Variable in class smile.stat.distribution.ChiSquareDistribution

The degrees of freedom.

nu - Variable in class smile.stat.distribution.TDistribution

The degree of freedom.

nu1 - Variable in class smile.stat.distribution.FDistribution

The degrees of freedom of chi-square distribution in numerator.

nu2 - Variable in class smile.stat.distribution.FDistribution

The degrees of freedom chi-square distribution in denominator.

nullDeviance - Variable in class smile.glm.GLM

The null deviance = 2 * (LogLikelihood(Saturated Model) - LogLikelihood(Null Model)).

nullDeviance(double[], double) - Method in interface smile.glm.model.Model

The NULL deviance function.

nullity() - Method in class smile.math.matrix.BigMatrix.SVD

Returns the dimension of null space.

nullity() - Method in class smile.math.matrix.fp32.Matrix.SVD

Returns the dimension of null space.

nullity() - Method in class smile.math.matrix.Matrix.SVD

Returns the dimension of null space.

nullspace() - Method in class smile.math.matrix.BigMatrix.SVD

Returns the matrix which columns are the orthonormal basis for the null space.

nullspace() - Method in class smile.math.matrix.fp32.Matrix.SVD

Returns the matrix which columns are the orthonormal basis for the null space.

nullspace() - Method in class smile.math.matrix.Matrix.SVD

Returns the matrix which columns are the orthonormal basis for the null space.

NUMBER - Static variable in class smile.swing.table.NumberCellRenderer

NumberCellRenderer - Class in smile.swing.table

Number renderer in JTable.

NumberCellRenderer() - Constructor for class smile.swing.table.NumberCellRenderer

Constructor.

NumberCellRenderer(int) - Constructor for class smile.swing.table.NumberCellRenderer

Constructor.

NumberCellRenderer(NumberFormat) - Constructor for class smile.swing.table.NumberCellRenderer

Constructor.

numberFormat(String) - Method in class smile.plot.vega.FormatConfig

Sets custom number format.

numberFormatType(String) - Method in class smile.plot.vega.FormatConfig

Sets custom number format type.

numClasses() - Method in class smile.classification.AbstractClassifier

numClasses() - Method in interface smile.classification.Classifier

Returns the number of classes.

numClasses() - Method in class smile.classification.DecisionTree

numClasses() - Method in class smile.classification.MLP

numClasses() - Method in class smile.classification.SVM

numDecoderLayers() - Method in record class smile.llm.Transformer.Options

Returns the value of the numDecoderLayers record component.

numEncoderLayers() - Method in record class smile.llm.Transformer.Options

Returns the value of the numEncoderLayers record component.

NumericalMeasure - Class in smile.data.measure

Numerical data, also called quantitative data.

NumericalMeasure(NumberFormat) - Constructor for class smile.data.measure.NumericalMeasure

Constructor.

numHeads() - Method in record class smile.llm.Transformer.Options

Returns the value of the numHeads record component.

numLayers() - Method in record class smile.vision.layer.MBConvConfig

Returns the value of the numLayers record component.

numTokens() - Method in record class smile.llm.Transformer.Options

Returns the value of the numTokens record component.

nystrom(T[], double[], T[], MercerKernel<T>, double) - Static method in class smile.regression.GaussianProcessRegression

Fits an approximate Gaussian process model with Nystrom approximation of kernel matrix.

nystrom(T[], double[], T[], MercerKernel<T>, double, boolean) - Static method in class smile.regression.GaussianProcessRegression

Fits an approximate Gaussian process model with Nystrom approximation of kernel matrix.

nystrom(T[], double[], T[], MercerKernel<T>, Properties) - Static method in class smile.regression.GaussianProcessRegression

Fits an approximate Gaussian process model with Nystrom approximation of kernel matrix.

nz() - Method in interface smile.data.SparseDataset

Returns the number of nonzero entries.

nz(int) - Method in interface smile.data.SparseDataset

Returns the number of nonzero entries in column j.

O

object(Serializable) - Static method in interface smile.io.Write

Writes an object to a temporary file and returns the path of file.

object(Serializable, Path) - Static method in interface smile.io.Write

Writes a serializable object to a file.

object(Class<?>) - Static method in class smile.data.type.DataTypes

Creates an object data type of a given class.

object(Path) - Static method in interface smile.io.Read

Reads a serialized object from a file.

Object - Enum constant in enum class smile.data.type.DataType.ID

Object type ID.

ObjectType - Class in smile.data.type

Object data type.

ObjectType - Static variable in class smile.data.type.DataTypes

Plain Object data type.

OCSVM<T> - Class in smile.base.svm

One-class support vector machine.

OCSVM(MercerKernel<T>, double, double) - Constructor for class smile.base.svm.OCSVM

Constructor.

of(boolean...) - Method in interface smile.data.DataFrame

Returns a new data frame with boolean indexing.

of(boolean...) - Static method in class smile.deep.tensor.Index

Returns the index of multiple elements in a dimension.

of(byte[][]) - Static method in interface smile.hash.SimHash

Returns the SimHash for a set of generic features (represented as byte[]).

of(byte[], long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor with given data and shape.

of(double) - Static method in class smile.math.Complex

Returns a Complex instance representing the specified value.

of(double[]) - Static method in interface smile.math.Histogram

Generate the histogram of given data.

of(double[]) - Method in class smile.math.kernel.BinarySparseGaussianKernel

of(double[]) - Method in class smile.math.kernel.BinarySparseHyperbolicTangentKernel

of(double[]) - Method in class smile.math.kernel.BinarySparseLaplacianKernel

of(double[]) - Method in class smile.math.kernel.BinarySparseLinearKernel

of(double[]) - Method in class smile.math.kernel.BinarySparseMaternKernel

of(double[]) - Method in class smile.math.kernel.BinarySparsePolynomialKernel

of(double[]) - Method in class smile.math.kernel.BinarySparseThinPlateSplineKernel

of(double[]) - Method in class smile.math.kernel.GaussianKernel

of(double[]) - Method in class smile.math.kernel.HellingerKernel

of(double[]) - Method in class smile.math.kernel.HyperbolicTangentKernel

of(double[]) - Method in class smile.math.kernel.LaplacianKernel

of(double[]) - Method in class smile.math.kernel.LinearKernel

of(double[]) - Method in class smile.math.kernel.MaternKernel

of(double[]) - Method in interface smile.math.kernel.MercerKernel

Returns the same kind kernel with the new hyperparameters.

of(double[]) - Method in class smile.math.kernel.PearsonKernel

of(double[]) - Method in class smile.math.kernel.PolynomialKernel

of(double[]) - Method in class smile.math.kernel.ProductKernel

of(double[]) - Method in class smile.math.kernel.SparseGaussianKernel

of(double[]) - Method in class smile.math.kernel.SparseHyperbolicTangentKernel

of(double[]) - Method in class smile.math.kernel.SparseLaplacianKernel

of(double[]) - Method in class smile.math.kernel.SparseLinearKernel

of(double[]) - Method in class smile.math.kernel.SparseMaternKernel

of(double[]) - Method in class smile.math.kernel.SparsePolynomialKernel

of(double[]) - Method in class smile.math.kernel.SparseThinPlateSplineKernel

of(double[]) - Method in class smile.math.kernel.SumKernel

of(double[]) - Method in class smile.math.kernel.ThinPlateSplineKernel

of(double[]) - Static method in class smile.plot.swing.Bar

Creates a bar plot.

of(double[]) - Static method in class smile.plot.swing.BarPlot

Creates a bar plot.

of(double[]) - Static method in class smile.plot.swing.Histogram

Creates a histogram plot.

of(double...) - Static method in class smile.plot.swing.Label

Creates a black label with coordinates as text.

of(double[]) - Static method in class smile.plot.swing.LinePlot

Creates a line plot with the index as the x coordinate.

of(double[]) - Static method in class smile.plot.swing.QQPlot

One sample Q-Q plot to standard normal distribution.

of(double[][]) - Static method in class smile.clustering.linkage.CompleteLinkage

Computes the proximity and the linkage.

of(double[][]) - Static method in class smile.clustering.linkage.SingleLinkage

Computes the proximity and the linkage.

of(double[][]) - Static method in class smile.clustering.linkage.UPGMALinkage

Computes the proximity and the linkage.

of(double[][]) - Static method in class smile.clustering.linkage.UPGMCLinkage

Computes the proximity and the linkage.

of(double[][]) - Static method in class smile.clustering.linkage.WardLinkage

Computes the proximity and the linkage.

of(double[][]) - Static method in class smile.clustering.linkage.WPGMALinkage

Computes the proximity and the linkage.

of(double[][]) - Static method in class smile.clustering.linkage.WPGMCLinkage

Computes the proximity and the linkage.

of(double[][]) - Static method in class smile.manifold.IsotonicMDS

Fits Kruskal's non-metric MDS with default k = 2, tolerance = 1E-4 and maxIter = 200.

of(double[][]) - Static method in class smile.manifold.MDS

Fits the classical multidimensional scaling.

of(double[][]) - Static method in class smile.manifold.SammonMapping

Fits Sammon's mapping with default k = 2, lambda = 0.2, tolerance = 1E-4 and maxIter = 100.

of(double[][]) - Static method in class smile.manifold.UMAP

Runs the UMAP algorithm.

of(double[][]) - Static method in class smile.math.matrix.BigMatrix

Returns a matrix from a two-dimensional array.

of(double[][]) - Static method in class smile.math.matrix.fp32.Matrix

Returns a matrix from a two-dimensional array.

of(double[][]) - Static method in class smile.math.matrix.Matrix

Returns a matrix from a two-dimensional array.

of(double[][]) - Static method in class smile.neighbor.KDTree

Return a KD-tree of the data.

of(double[]...) - Static method in class smile.plot.swing.BoxPlot

Create a plot canvas with multiple box plots of given data.

of(double[][]) - Static method in class smile.plot.swing.Contour

Creates a contour plot with 10 isolines.

of(double[][]) - Static method in class smile.plot.swing.Heatmap

Constructor.

of(double[][]) - Static method in class smile.plot.swing.Hexmap

Creates a hexmap with 16-color jet color palette.

of(double[][]) - Static method in class smile.plot.swing.Histogram3D

Creates a 3D histogram plot.

of(double[][]) - Static method in class smile.plot.swing.Line

Creates a Line with solid stroke and black color.

of(double[][]) - Static method in class smile.plot.swing.LinePlot

Creates a line plot.

of(double[][]) - Static method in class smile.plot.swing.Point

Creates a Point with circle mark and black color.

of(double[][]) - Static method in class smile.plot.swing.ScatterPlot

Create a scatter plot.

of(double[][]) - Static method in class smile.plot.swing.Staircase

Creates a Staircase with solid stroke and black color.

of(double[][]) - Static method in class smile.plot.swing.StaircasePlot

Creates a line plot.

of(double[][][]) - Static method in class smile.plot.swing.Grid

Creates a grid with black lines.

of(double[][], char) - Static method in class smile.plot.swing.Line

Creates a Line.

of(double[][], char) - Static method in class smile.plot.swing.Point

Creates a Point with black color.

of(double[][], char) - Static method in class smile.plot.swing.ScatterPlot

Create a scatter plot.

of(double[][], char, Color) - Static method in class smile.plot.swing.ScatterPlot

Create a scatter plot.

of(double[][], double[][], double, double, double, int) - Static method in class smile.manifold.SammonMapping

Fits Sammon's mapping.

of(double[][], double[][], double, int) - Static method in class smile.manifold.IsotonicMDS

Fits Kruskal's non-metric MDS.

of(double[][], double[], int) - Static method in interface smile.deep.Dataset

Creates a dataset of numeric arrays.

of(double[][], int) - Static method in class smile.manifold.IsoMap

Runs the C-Isomap algorithm with Euclidean distance.

of(double[][], int) - Static method in class smile.manifold.IsotonicMDS

Fits Kruskal's non-metric MDS.

of(double[][], int) - Static method in class smile.manifold.LaplacianEigenmap

Laplacian Eigenmaps with discrete weights.

of(double[][], int) - Static method in class smile.manifold.LLE

Runs the LLE algorithm.

of(double[][], int) - Static method in class smile.manifold.MDS

Fits the classical multidimensional scaling.

of(double[][], int) - Static method in class smile.manifold.SammonMapping

Fits Sammon's mapping.

of(double[][], int) - Static method in class smile.manifold.UMAP

Runs the UMAP algorithm.

of(double[][], int) - Static method in class smile.plot.swing.Contour

Creates a contour plot.

of(double[][], int) - Static method in class smile.plot.swing.Heatmap

Creates a heatmap with jet color palette.

of(double[][], int) - Static method in class smile.plot.swing.Hexmap

Creates a hexmap with the jet color palette.

of(double[][], int) - Static method in class smile.plot.swing.Surface

Creates a regular mesh surface with the jet color palette.

of(double[][], int[][]) - Static method in class smile.plot.swing.Wireframe

Constructor.

of(double[][], int[], char) - Static method in class smile.plot.swing.ScatterPlot

Creates a scatter plot of multiple groups of data.

of(double[][], int[], int) - Static method in interface smile.deep.Dataset

Creates a dataset of numeric arrays.

of(double[][], int, boolean) - Static method in class smile.manifold.MDS

Fits the classical multidimensional scaling.

of(double[][], int, boolean) - Static method in class smile.plot.swing.Histogram3D

Creates a 3D histogram plot.

of(double[][], int, boolean, Color[]) - Static method in class smile.plot.swing.Histogram3D

Creates a 3D histogram plot.

of(double[][], int, double, double, double, int) - Static method in class smile.manifold.SammonMapping

Fits Sammon's mapping.

of(double[][], int, double, int) - Static method in class smile.manifold.IsotonicMDS

Fits Kruskal's non-metric MDS.

of(double[][], int, int) - Static method in class smile.manifold.LLE

Runs the LLE algorithm.

of(double[][], int, int, boolean) - Static method in class smile.manifold.IsoMap

Runs the Isomap algorithm.

of(double[][], int, int, double) - Static method in class smile.manifold.LaplacianEigenmap

Laplacian Eigenmap with Gaussian kernel.

of(double[][], int, int, int, double, double, double, int, double) - Static method in class smile.manifold.UMAP

Runs the UMAP algorithm.

of(double[][], int, Color[]) - Static method in class smile.plot.swing.Histogram3D

Creates a 3D histogram plot.

of(double[][], Color) - Static method in class smile.plot.swing.Line

Creates a Line.

of(double[][], Color) - Static method in class smile.plot.swing.LinePlot

Creates a line plot.

of(double[][], Color) - Static method in class smile.plot.swing.Point

Creates a Point with circle mark.

of(double[][], Color) - Static method in class smile.plot.swing.ScatterPlot

Create a scatter plot.

of(double[][], Color[]) - Static method in class smile.plot.swing.Heatmap

Constructor.

of(double[][], Color[]) - Static method in class smile.plot.swing.Hexmap

Constructor.

of(double[][], Color[]) - Static method in class smile.plot.swing.Surface

Creates a regular mesh surface.

of(double[][], Color, String) - Static method in class smile.plot.swing.StaircasePlot

Creates a line plot.

of(double[][], String...) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a 2-dimensional array.

of(double[][], String[]) - Static method in class smile.plot.swing.BarPlot

Creates a bar plot of multiple groups/colors.

of(double[][], String[], char) - Static method in class smile.plot.swing.ScatterPlot

Creates a scatter plot of multiple groups of data.

of(double[][], Properties) - Static method in class smile.manifold.IsotonicMDS

Fits Kruskal's non-metric MDS.

of(double[][], Properties) - Static method in class smile.manifold.MDS

Fits the classical multidimensional scaling.

of(double[][], Properties) - Static method in class smile.manifold.SammonMapping

Fits Sammon's mapping.

of(double[][], Line.Style) - Static method in class smile.plot.swing.Line

Creates a Line.

of(double[][], Line.Style) - Static method in class smile.plot.swing.LinePlot

Creates a line plot.

of(double[][], Line.Style, Color) - Static method in class smile.plot.swing.Line

Creates a Line.

of(double[][], Line.Style, Color) - Static method in class smile.plot.swing.LinePlot

Creates a line plot.

of(double[][], Line.Style, Color, String) - Static method in class smile.plot.swing.LinePlot

Creates a line plot.

of(double[], double[]) - Static method in interface smile.math.Histogram

Generate the histogram of n bins.

of(double[], double[]) - Static method in class smile.plot.swing.QQPlot

Two sample Q-Q plot.

of(double[], double[]) - Static method in class smile.validation.metric.MAD

Calculates the mean absolute deviation error.

of(double[], double[]) - Static method in class smile.validation.metric.MSE

Calculates the mean squared error.

of(double[], double[]) - Static method in class smile.validation.metric.R2

Calculates the R squared coefficient.

of(double[], double[]) - Static method in class smile.validation.metric.RMSE

Calculates the root mean squared error.

of(double[], double[]) - Static method in class smile.validation.metric.RSS

Calculates the residual sum of squares.

of(double[], double[], boolean) - Static method in class smile.plot.swing.Histogram

Creates a histogram plot.

of(double[], double[], boolean, Color) - Static method in class smile.plot.swing.Histogram

Creates a histogram plot.

of(double[], double[], double[][]) - Static method in class smile.plot.swing.Contour

Creates a contour plot with 10 isolines.

of(double[], double[], double[][]) - Static method in class smile.plot.swing.Heatmap

Constructor.

of(double[], double[], double[][]) - Static method in class smile.plot.swing.Surface

Creates an irregular mesh grid.

of(double[], double[], double[][], int) - Static method in class smile.plot.swing.Contour

Creates a contour plot.

of(double[], double[], double[][], int) - Static method in class smile.plot.swing.Heatmap

Constructor.

of(double[], double[], double[][], int) - Static method in class smile.plot.swing.Surface

Creates an irregular mesh surface with the jet color palette.

of(double[], double[], double[][], Color[]) - Static method in class smile.plot.swing.Surface

Creates an irregular mesh surface.

of(double[], int) - Static method in interface smile.math.Histogram

Generate the histogram of n bins.

of(double[], int, boolean) - Static method in class smile.plot.swing.Histogram

Creates a histogram plot.

of(double[], int, boolean, Color) - Static method in class smile.plot.swing.Histogram

Creates a histogram plot.

of(double[], long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor with given data and shape.

of(double[], Color) - Static method in class smile.plot.swing.LinePlot

Creates a line plot with the index as the x coordinate.

of(double[], StructType) - Static method in interface smile.data.Tuple

Returns a double array based tuple.

of(double[], Line.Style) - Static method in class smile.plot.swing.LinePlot

Creates a line plot with the index as the x coordinate.

of(double[], Line.Style, Color) - Static method in class smile.plot.swing.LinePlot

Creates a line plot with the index as the x coordinate.

of(double[], Line.Style, Color, String) - Static method in class smile.plot.swing.LinePlot

Creates a line plot with the index as the x coordinate.

of(double[], Distribution) - Static method in class smile.plot.swing.QQPlot

One sample Q-Q plot to given distribution.

of(double, double) - Static method in class smile.math.Complex

Returns a Complex instance representing the specified value.

of(double, double, double[], double[]) - Static method in class smile.validation.RegressionMetrics

Computes the regression metrics.

of(double, double, int[], int[]) - Static method in class smile.validation.ClassificationMetrics

Computes the classification metrics.

of(double, double, int[], int[], double[][]) - Static method in class smile.validation.ClassificationMetrics

Computes the soft classification metrics.

of(double, int[][]) - Static method in class smile.association.FPTree

One-step construction of FP-tree if the database is available in main memory.

of(double, int[], int[]) - Static method in class smile.validation.metric.FScore

Calculates the F1 score.

of(double, Supplier<Stream<int[]>>) - Static method in class smile.association.FPTree

One-step construction of FP-tree if the database is available as stream.

of(double, M, Formula, DataFrame) - Static method in class smile.validation.ClassificationMetrics

Validates a model on a test data.

of(double, M, Formula, DataFrame) - Static method in class smile.validation.RegressionMetrics

Trains and validates a model on a train/validation split.

of(double, M, T[], double[]) - Static method in class smile.validation.RegressionMetrics

Validates a model on a test data.

of(double, M, T[], int[]) - Static method in class smile.validation.ClassificationMetrics

Validates a model on a test data.

of(float[]) - Static method in interface smile.math.Histogram

Generate the histogram of given data.

of(float[][]) - Static method in class smile.math.matrix.fp32.Matrix

Returns a matrix from a two-dimensional array.

of(float[][], float[], int) - Static method in interface smile.deep.Dataset

Creates a dataset of numeric arrays.

of(float[][], int[], int) - Static method in interface smile.deep.Dataset

Creates a dataset of numeric arrays.

of(float[][], String...) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a 2-dimensional array.

of(float[], float[]) - Static method in interface smile.math.Histogram

Generate the histogram of n bins.

of(float[], int) - Static method in interface smile.math.Histogram

Generate the histogram of n bins.

of(float[], long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor with given data and shape.

of(int) - Static method in class smile.deep.tensor.Index

Returns the index of a single element in a dimension.

of(int) - Static method in class smile.util.IntSet

Returns the IntSet of [0, k).

of(int) - Static method in interface smile.validation.LOOCV

Returns the training sample index for each round.

of(int...) - Method in interface smile.data.DataFrame

Returns a new data frame with row indexing.

of(int...) - Static method in class smile.deep.tensor.Index

Returns the index of multiple elements in a dimension.

of(int[]) - Static method in interface smile.math.Histogram

Generate the histogram of given data.

of(int[]) - Static method in class smile.plot.swing.Bar

Creates a bar plot.

of(int[]) - Static method in class smile.plot.swing.BarPlot

Creates a bar plot.

of(int[]) - Static method in class smile.plot.swing.Histogram

Creates a histogram plot.

of(int[]) - Static method in class smile.util.IntSet

Finds the unique values from samples.

of(int[][]) - Static method in interface smile.data.BinarySparseDataset

Returns a default implementation of BinarySparseDataset without targets.

of(int[][], String...) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a 2-dimensional array.

of(int[], double[]) - Static method in interface smile.math.Histogram

Generate the histogram of n bins.

of(int[], double[]) - Static method in class smile.validation.metric.AUC

Calculates AUC for binary classifier.

of(int[], double[]) - Static method in class smile.validation.metric.LogLoss

Calculates the Log Loss for binary classifier.

of(int[], double[][]) - Static method in interface smile.validation.metric.CrossEntropy

Calculates the cross entropy for multiclass classifier.

of(int[], double[], boolean) - Static method in class smile.plot.swing.Histogram

Creates a histogram plot.

of(int[], double[], boolean, Color) - Static method in class smile.plot.swing.Histogram

Creates a histogram plot.

of(int[], int) - Static method in interface smile.math.Histogram

Generate the histogram of k bins.

of(int[], int) - Static method in interface smile.validation.Bootstrap

Stratified bootstrap sampling.

of(int[], int[]) - Static method in class smile.plot.swing.QQPlot

Two sample Q-Q plot.

of(int[], int[]) - Static method in class smile.stat.GoodTuring

Good–Turing frequency estimation.

of(int[], int[]) - Static method in class smile.validation.metric.Accuracy

Calculates the classification accuracy.

of(int[], int[]) - Static method in class smile.validation.metric.AdjustedRandIndex

Calculates the adjusted rand index.

of(int[], int[]) - Static method in class smile.validation.metric.ConfusionMatrix

Creates the confusion matrix.

of(int[], int[]) - Static method in class smile.validation.metric.Error

Calculates the number of errors.

of(int[], int[]) - Static method in class smile.validation.metric.Fallout

Calculates the false alarm rate.

of(int[], int[]) - Static method in class smile.validation.metric.FDR

Calculates the false discovery rate.

of(int[], int[]) - Static method in class smile.validation.metric.MatthewsCorrelation

Calculates Matthews correlation coefficient.

of(int[], int[]) - Static method in class smile.validation.metric.MutualInformation

Calculates the mutual information.

of(int[], int[]) - Static method in class smile.validation.metric.Precision

Calculates the precision.

of(int[], int[]) - Static method in class smile.validation.metric.RandIndex

Calculates the rand index.

of(int[], int[]) - Static method in class smile.validation.metric.Recall

Calculates the recall/sensitivity.

of(int[], int[]) - Static method in class smile.validation.metric.Sensitivity

Calculates the sensitivity.

of(int[], int[]) - Static method in class smile.validation.metric.Specificity

Calculates the specificity.

of(int[], int, boolean) - Static method in class smile.plot.swing.Histogram

Creates a histogram plot.

of(int[], int, boolean, Color) - Static method in class smile.plot.swing.Histogram

Creates a histogram plot.

of(int[], long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor with given data and shape.

of(int[], StructType) - Static method in interface smile.data.Tuple

Returns an integer array based tuple.

of(int[], DiscreteDistribution) - Static method in class smile.plot.swing.QQPlot

One sample Q-Q plot to given discrete distribution.

of(int, int) - Static method in interface smile.validation.Bootstrap

Bootstrap sampling.

of(int, int) - Static method in interface smile.validation.CrossValidation

Creates a k-fold cross validation.

of(int, int[][]) - Static method in class smile.association.FPTree

One-step construction of FP-tree if the database is available in main memory.

of(int, int, int) - Method in interface smile.vq.Neighborhood

Returns the changing rate of neighborhood at a given iteration.

of(int, int, String) - Static method in class smile.base.mlp.Layer

Returns the layer builders given a string representation such as "Input(10, 0.2)|ReLU(50, 0.5)|Sigmoid(30, 0.5)|...".

of(int, int, String...) - Static method in class smile.feature.extraction.RandomProjection

Generates a non-sparse random projection.

of(int, Supplier<Stream<int[]>>) - Static method in class smile.association.FPTree

One-step construction of FP-tree if the database is available as stream.

of(long) - Static method in class smile.deep.tensor.Index

Returns the index of a single element in a dimension.

of(long...) - Static method in class smile.deep.tensor.Index

Returns the index of multiple elements in a dimension.

of(long[], long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor with given data and shape.

of(short[], long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor with given data and shape.

of(D[], double[]) - Static method in interface smile.data.Dataset

Returns a default implementation of Dataset from a collection.

of(D[], float[]) - Static method in interface smile.data.Dataset

Returns a default implementation of Dataset from a collection.

of(D[], int[]) - Static method in interface smile.data.Dataset

Returns a default implementation of Dataset from a collection.

of(D[], T[]) - Static method in interface smile.data.Dataset

Returns a default implementation of Dataset from a collection.

of(Class) - Static method in interface smile.data.type.DataType

Returns the DataType of a class.

of(Object[], StructType) - Static method in interface smile.data.Tuple

Returns an object array based tuple.

of(String) - Static method in class smile.data.formula.Formula

Parses a formula string.

of(String) - Static method in interface smile.data.type.DataType

Returns a DataType from its string representation.

of(String) - Static method in interface smile.math.kernel.MercerKernel

Returns a kernel function.

of(String) - Static method in interface smile.math.TimeFunction

Parses a time function.

of(String) - Static method in interface smile.nlp.keyword.CooccurrenceKeywords

Returns the top 10 keywords.

of(String[], double[][]) - Static method in class smile.plot.swing.TextPlot

Create a text plot.

of(String[], String[], double[][]) - Static method in class smile.plot.swing.Heatmap

Constructor.

of(String[], String[], double[][], int) - Static method in class smile.plot.swing.Heatmap

Constructor.

of(String, boolean[]) - Static method in interface smile.data.vector.BooleanVector

Creates a named boolean vector.

of(String, byte[]) - Static method in interface smile.data.vector.ByteVector

Creates a named byte vector.

of(String, char[]) - Static method in interface smile.data.vector.CharVector

Creates a named char vector.

of(String, double[]) - Static method in interface smile.data.vector.DoubleVector

Creates a named double vector.

of(String, double[]) - Static method in class smile.math.Scaler

Returns the scaler.

of(String, double[]) - Static method in class smile.plot.swing.Label

Creates a black label centered at the coordinates.

of(String, double[], double, double, double) - Static method in class smile.plot.swing.Label

Creates a black label with system default font.

of(String, float[]) - Static method in interface smile.data.vector.FloatVector

Creates a named float vector.

of(String, int) - Static method in interface smile.nlp.keyword.CooccurrenceKeywords

Returns a given number of top keywords.

of(String, int[]) - Static method in interface smile.data.vector.IntVector

Creates a named integer vector.

of(String, long[]) - Static method in interface smile.data.vector.LongVector

Creates a named long vector.

of(String, short[]) - Static method in interface smile.data.vector.ShortVector

Creates a named short integer vector.

of(String, Class<?>, T[]) - Static method in interface smile.data.vector.Vector

Creates a named vector.

of(String, String...) - Static method in class smile.data.formula.Formula

Factory method.

of(String, String...) - Static method in interface smile.data.vector.StringVector

Creates a named string vector.

of(String, String, boolean) - Static method in class smile.plot.vega.Predicate

Test if a field in the data point satisfies certain conditions.

of(String, String, double) - Static method in class smile.plot.vega.Predicate

Test if a field in the data point satisfies certain conditions.

of(String, String, Class<R>, Function<T, R>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given variable.

of(String, String, String) - Static method in class smile.plot.vega.Predicate

Test if a field in the data point satisfies certain conditions.

of(String, String, String, Class<R>, BiFunction<T, U, R>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given variables.

of(String, String, String, ToDoubleBiFunction<T, U>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given variables.

of(String, String, String, ToIntBiFunction<T, U>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given variables.

of(String, String, String, ToLongBiFunction<T, U>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given variables.

of(String, String, ToDoubleFunction<T>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given variable.

of(String, String, ToIntFunction<T>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given variable.

of(String, String, ToLongFunction<T>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given variable.

of(String, DoubleStream) - Static method in interface smile.data.vector.DoubleVector

Creates a named double vector.

of(String, IntStream) - Static method in interface smile.data.vector.IntVector

Creates a named integer vector.

of(String, LongStream) - Static method in interface smile.data.vector.LongVector

Creates a named long integer vector.

of(String, Term...) - Static method in class smile.data.formula.Formula

Factory method.

of(String, Term, Class<R>, Function<T, R>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given term.

of(String, Term, ToDoubleFunction<T>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given term.

of(String, Term, ToIntFunction<T>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given term.

of(String, Term, ToLongFunction<T>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given term.

of(String, Term, Term, Class<R>, BiFunction<T, U, R>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given terms.

of(String, Term, Term, ToDoubleBiFunction<T, U>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given terms.

of(String, Term, Term, ToIntBiFunction<T, U>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given terms.

of(String, Term, Term, ToLongBiFunction<T, U>) - Static method in interface smile.data.formula.Terms

Returns a term that applies a lambda on given terms.

of(String, DataType, T[]) - Static method in interface smile.data.vector.Vector

Creates a named vector.

of(Path) - Static method in class smile.nlp.embedding.GloVe

Loads a GloVe model.

of(Path) - Static method in class smile.nlp.embedding.Word2Vec

Loads a pre-trained word2vec model from binary file of ByteOrder.LITTLE_ENDIAN.

of(Path, ByteOrder) - Static method in class smile.nlp.embedding.Word2Vec

Loads a pre-trained word2vec model from binary file.

of(JDBCType, boolean, String) - Static method in interface smile.data.type.DataType

Returns the DataType of a JDBC type.

of(ResultSet) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a JDBC ResultSet.

of(ResultSet, StructType) - Static method in interface smile.data.Tuple

Returns the current row of a JDBC ResultSet as a tuple.

of(Collection<String[]>, int, int) - Static method in class smile.nlp.collocation.NGram

Extracts n-gram phrases by an Apiori-like algorithm.

of(Collection<Map<String, T>>, StructType) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a set of Maps.

of(Collection<SampleInstance<D, T>>) - Static method in interface smile.data.Dataset

Returns a default implementation of Dataset from a collection.

of(Collection<SampleInstance<int[], T>>) - Static method in interface smile.data.BinarySparseDataset

Returns a default implementation of BinarySparseDataset.

of(Collection<SampleInstance<SparseArray, T>>) - Static method in interface smile.data.SparseDataset

Returns a default implementation of SparseDataset without targets.

of(Collection<SampleInstance<SparseArray, T>>, int) - Static method in interface smile.data.SparseDataset

Returns a default implementation of SparseDataset without targets.

of(List<? extends Tuple>) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a set of tuples.

of(List<? extends Tuple>, StructType) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a set of tuples.

of(List<D>, List<T>) - Static method in interface smile.data.Dataset

Returns a default implementation of Dataset from a collection.

of(List<T>, Class<T>) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a collection.

of(List<T>, Distance<T>) - Static method in class smile.neighbor.LinearSearch

Return linear nearest neighbor search.

of(List<T>, Metric<T>) - Static method in class smile.neighbor.BKTree

Return a BK-tree of the data.

of(List<T>, Metric<T>) - Static method in class smile.neighbor.CoverTree

Return a cover tree of the data.

of(List<T>, Metric<T>, double) - Static method in class smile.neighbor.CoverTree

Return a cover tree of the data.

of(Stream<? extends Tuple>) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a stream of tuples.

of(Stream<? extends Tuple>, StructType) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a stream of tuples.

of(Stream<SparseArray>) - Static method in interface smile.data.SparseDataset

Returns a default implementation of SparseDataset.

of(M, Formula, DataFrame) - Static method in class smile.validation.ClassificationMetrics

Validates a model on a test data.

of(M, Formula, DataFrame) - Static method in class smile.validation.RegressionMetrics

Trains and validates a model on a train/validation split.

of(M, T[], double[]) - Static method in class smile.validation.RegressionMetrics

Validates a model on a test data.

of(M, T[], int[]) - Static method in class smile.validation.ClassificationMetrics

Validates a model on a test data.

of(KernelMachine<double[]>) - Static method in class smile.base.svm.LinearKernelMachine

Creates a linear kernel machine.

of(DataFrame, String, String, char, Color) - Static method in class smile.plot.swing.ScatterPlot

Creates a scatter plot from a data frame.

of(DataFrame, String, String, String, char) - Static method in class smile.plot.swing.ScatterPlot

Creates a scatter plot from a data frame.

of(DataFrame, String, String, String, char, Color) - Static method in class smile.plot.swing.ScatterPlot

Creates a scatter plot from a data frame.

of(DataFrame, String, String, String, String, char) - Static method in class smile.plot.swing.ScatterPlot

Creates a scatter plot from a data frame.

of(Formula, DataFrame, int) - Static method in interface smile.deep.Dataset

Returns a dataset.

of(Formula, DataFrame, Properties, Classifier.Trainer<double[], ?>) - Static method in interface smile.classification.DataFrameClassifier

Fits a vector classifier on data frame.

of(Formula, DataFrame, Properties, Regression.Trainer<double[], ?>) - Static method in interface smile.regression.DataFrameRegression

Fits a vector regression model on data frame.

of(Formula, DataFrame, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in class smile.validation.ClassificationValidation

Trains and validates a model on a train/validation split.

of(Formula, DataFrame, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in class smile.validation.RegressionValidation

Trains and validates a model on a train/validation split.

of(Term, Term...) - Static method in class smile.data.formula.Formula

Factory method.

of(StructField, boolean[]) - Static method in interface smile.data.vector.BooleanVector

Creates a named boolean vector.

of(StructField, byte[]) - Static method in interface smile.data.vector.ByteVector

Creates a named byte vector.

of(StructField, char[]) - Static method in interface smile.data.vector.CharVector

Creates a named char vector.

of(StructField, double[]) - Static method in interface smile.data.vector.DoubleVector

Creates a named double vector.

of(StructField, float[]) - Static method in interface smile.data.vector.FloatVector

Creates a named float vector.

of(StructField, int[]) - Static method in interface smile.data.vector.IntVector

Creates a named integer vector.

of(StructField, long[]) - Static method in interface smile.data.vector.LongVector

Creates a named long integer vector.

of(StructField, short[]) - Static method in interface smile.data.vector.ShortVector

Creates a named short integer vector.

of(StructField, String...) - Static method in interface smile.data.vector.StringVector

Creates a named string vector.

of(StructField, DoubleStream) - Static method in interface smile.data.vector.DoubleVector

Creates a named double vector.

of(StructField, IntStream) - Static method in interface smile.data.vector.IntVector

Creates a named integer vector.

of(StructField, LongStream) - Static method in interface smile.data.vector.LongVector

Creates a named long integer vector.

of(StructField, T[]) - Static method in interface smile.data.vector.Vector

Creates a named vector.

of(BaseVector...) - Static method in interface smile.data.DataFrame

Creates a DataFrame from a set of vectors.

of(Tensor) - Static method in class smile.deep.tensor.Index

Returns the tensor index along a dimension.

of(Complex...) - Static method in class smile.math.Complex.Array

Creates a packed array of complex values.

of(IMatrix) - Static method in class smile.math.matrix.PageRank

Calculates the page rank vector.

of(IMatrix, double[]) - Static method in class smile.math.matrix.PageRank

Calculates the page rank vector.

of(IMatrix, double[], double, double, int) - Static method in class smile.math.matrix.PageRank

Calculates the page rank vector.

of(SparseMatrix) - Static method in class smile.graph.AdjacencyList

Converts the sparse matrix to a graph.

of(SparseMatrix) - Static method in class smile.plot.swing.SparseMatrixPlot

Creates a sparse matrix plot with blue color for nonzero entries.

of(SparseMatrix, int) - Static method in class smile.plot.swing.SparseMatrixPlot

Creates a sparse matrix plot with the jet color palette.

of(Corpus, double, int) - Static method in class smile.nlp.collocation.Bigram

Finds bigram collocations in the given corpus whose p-value is less than the given threshold.

of(Corpus, int, int) - Static method in class smile.nlp.collocation.Bigram

Finds top k bigram collocations in the given corpus.

of(SparseArray[]) - Static method in interface smile.data.SparseDataset

Returns a default implementation of SparseDataset without targets.

of(SparseArray[], int) - Static method in interface smile.data.SparseDataset

Returns a default implementation of SparseDataset without targets.

of(Bag[], Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in class smile.validation.ClassificationValidation

Trains and validates a model on multiple train/validation split.

of(Bag[], Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in class smile.validation.RegressionValidation

Trains and validates a model on multiple train/validation split.

of(Bag[], T[], double[], BiFunction<T[], double[], M>) - Static method in class smile.validation.RegressionValidation

Trains and validates a model on multiple train/validation split.

of(Bag[], T[], int[], BiFunction<T[], int[], M>) - Static method in class smile.validation.ClassificationValidation

Trains and validates a model on multiple train/validation split.

of(T[], double[], T[], double[], BiFunction<T[], double[], M>) - Static method in class smile.validation.RegressionValidation

Trains and validates a model on a train/validation split.

of(T[], int[], T[], int[], BiFunction<T[], int[], M>) - Static method in class smile.validation.ClassificationValidation

Trains and validates a model on a train/validation split.

of(T[], Distance<T>) - Static method in class smile.clustering.linkage.CompleteLinkage

Computes the proximity and the linkage.

of(T[], Distance<T>) - Static method in class smile.clustering.linkage.SingleLinkage

Computes the proximity and the linkage.

of(T[], Distance<T>) - Static method in class smile.clustering.linkage.UPGMALinkage

Computes the proximity and the linkage.

of(T[], Distance<T>) - Static method in class smile.clustering.linkage.UPGMCLinkage

Computes the proximity and the linkage.

of(T[], Distance<T>) - Static method in class smile.clustering.linkage.WardLinkage

Computes the proximity and the linkage.

of(T[], Distance<T>) - Static method in class smile.clustering.linkage.WPGMALinkage

Computes the proximity and the linkage.

of(T[], Distance<T>) - Static method in class smile.clustering.linkage.WPGMCLinkage

Computes the proximity and the linkage.

of(T[], Distance<T>) - Static method in class smile.manifold.UMAP

Runs the UMAP algorithm.

of(T[], Distance<T>) - Static method in class smile.neighbor.LinearSearch

Return linear nearest neighbor search.

of(T[], Distance<T>, int) - Static method in class smile.manifold.IsoMap

Runs the C-Isomap algorithm.

of(T[], Distance<T>, int) - Static method in class smile.manifold.LaplacianEigenmap

Laplacian Eigenmaps with discrete weights.

of(T[], Distance<T>, int) - Static method in class smile.manifold.UMAP

Runs the UMAP algorithm.

of(T[], Distance<T>, int, int, boolean) - Static method in class smile.manifold.IsoMap

Runs the Isomap algorithm.

of(T[], Distance<T>, int, int, double) - Static method in class smile.manifold.LaplacianEigenmap

Laplacian Eigenmap with Gaussian kernel.

of(T[], Distance<T>, int, int, int, double, double, double, int, double) - Static method in class smile.manifold.UMAP

Runs the UMAP algorithm.

of(T[], Metric<T>) - Static method in class smile.neighbor.BKTree

Return a BK-tree of the data.

of(T[], Metric<T>) - Static method in class smile.neighbor.CoverTree

Return a cover tree of the data.

of(T[], Metric<T>, double) - Static method in class smile.neighbor.CoverTree

Return a cover tree of the data.

of(T[], RadialBasisFunction[], Metric<T>) - Static method in class smile.base.rbf.RBF

Makes a set of RBF neurons.

of(T[], RadialBasisFunction, Metric<T>) - Static method in class smile.base.rbf.RBF

Makes a set of RBF neurons.

of(T, int, double) - Static method in class smile.neighbor.Neighbor

Creates a neighbor object, of which key and object are the same.

offset() - Method in class smile.math.kernel.HyperbolicTangent

Returns the offset of kernel.

offset() - Method in class smile.math.kernel.Polynomial

Returns the offset of kernel.

offset(double) - Method in class smile.plot.vega.Axis

Sets the offset, in pixels, by which to displace the axis from the edge of the enclosing group or data rectangle.

offset(double) - Method in class smile.plot.vega.Legend

Sets the offset, in pixels, by which to displace the legend from the edge of the enclosing group or data rectangle.

offset(String) - Method in class smile.plot.vega.StackTransform

Sets the mode for stacking marks.

OK_OPTION - Static variable in class smile.swing.FontChooser

Return value from showDialog().

ols(double[], int) - Static method in class smile.timeseries.AR

Fits an autoregressive model with least squares method.

ols(double[], int, boolean) - Static method in class smile.timeseries.AR

Fits an autoregressive model with least squares method.

OLS - Class in smile.regression

Ordinary least squares.

OLS - Enum constant in enum class smile.timeseries.AR.Method

Ordinary least squares.

OLS() - Constructor for class smile.regression.OLS

omega() - Method in class smile.math.kernel.PearsonKernel

Returns the tailing factor of the peak.

omit(double[], double) - Static method in class smile.math.MathEx

Returns a new array without the specified value.

omit(float[], float) - Static method in class smile.math.MathEx

Returns a new array without the specified value.

omit(int[], int) - Static method in class smile.math.MathEx

Returns a new array without the specified value.

omitNaN(double[]) - Static method in class smile.math.MathEx

Returns a new array without NaN values.

omitNaN(float[]) - Static method in class smile.math.MathEx

Returns a new array without NaN values.

omitNullRows() - Method in interface smile.data.DataFrame

Returns a new data frame without rows that have null/missing values.

ONE_HOT - Enum constant in enum class smile.data.CategoricalEncoder

One hot encoding.

oneOf(String, double...) - Static method in class smile.plot.vega.Predicate

Test if a field in the data point satisfies certain conditions.

oneOf(String, String...) - Static method in class smile.plot.vega.Predicate

Test if a field in the data point satisfies certain conditions.

ones(long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor filled with all ones.

ones(Tensor.Options, long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor filled with all ones.

OneVersusOne<T> - Class in smile.classification

One-vs-one strategy for reducing the problem of multiclass classification to multiple binary classification problems.

OneVersusOne(Classifier<T>[][], PlattScaling[][]) - Constructor for class smile.classification.OneVersusOne

Constructor.

OneVersusOne(Classifier<T>[][], PlattScaling[][], IntSet) - Constructor for class smile.classification.OneVersusOne

Constructor.

OneVersusRest<T> - Class in smile.classification

One-vs-rest (or one-vs-all) strategy for reducing the problem of multiclass classification to multiple binary classification problems.

OneVersusRest(Classifier<T>[], PlattScaling[]) - Constructor for class smile.classification.OneVersusRest

Constructor.

OneVersusRest(Classifier<T>[], PlattScaling[], IntSet) - Constructor for class smile.classification.OneVersusRest

Constructor.

online() - Method in interface smile.classification.Classifier

Returns true if this is an online learner.

online() - Method in class smile.classification.DiscreteNaiveBayes

online() - Method in class smile.classification.LogisticRegression

online() - Method in class smile.classification.Maxent

online() - Method in class smile.classification.MLP

online() - Method in class smile.classification.SparseLogisticRegression

online() - Method in class smile.regression.LinearModel

online() - Method in class smile.regression.MLP

online() - Method in interface smile.regression.Regression

Returns true if this is an online learner.

oob - Variable in class smile.validation.Bag

The index of testing instances.

op() - Method in record class smile.plot.vega.WindowTransformField

Returns the value of the op record component.

op(String) - Method in class smile.plot.vega.PivotTransform

Sets the aggregation operation to apply to grouped value field values.

opacity(double) - Method in class smile.plot.vega.Background

Sets the overall opacity.

opacity(double) - Method in class smile.plot.vega.Mark

Sets the overall opacity.

opacity(double) - Method in class smile.plot.vega.ViewConfig

Sets the overall opacity.

open - Variable in enum class smile.nlp.pos.PennTreebankPOS

True if the POS is a open class.

OpenBLAS - Class in smile.math.blas.openblas

OpenBLAS library wrapper.

OpenBLAS() - Constructor for class smile.math.blas.openblas.OpenBLAS

OPENING_PARENTHESIS - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Punctuation ( [ {

OPENING_QUOTATION - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Punctuation ` or ``

Operator - Class in smile.data.formula

The infix bifunction term.

Operator(String, Term, Term) - Constructor for class smile.data.formula.Operator

Constructor.

Optimizer - Class in smile.deep

Optimizer functions.

Optimizer - Interface in smile.base.mlp.optimizer

The neural network optimizer.

Options() - Constructor for class smile.deep.tensor.Tensor.Options

Constructor with default values for every axis.

Options(int) - Constructor for record class smile.llm.Transformer.Options

Constructor with default values.

Options(int, int, int) - Constructor for record class smile.vision.layer.Conv2dNormActivation.Options

Constructor.

Options(int, int, int, int, int, int, double, String) - Constructor for record class smile.llm.Transformer.Options

Creates an instance of a Options record class.

Options(int, int, int, int, int, int, int, IntFunction<Layer>, ActivationFunction) - Constructor for record class smile.vision.layer.Conv2dNormActivation.Options

Custom constructor.

Options(int, int, int, int, int, IntFunction<Layer>, ActivationFunction) - Constructor for record class smile.vision.layer.Conv2dNormActivation.Options

Constructor.

Options(int, int, int, int, IntFunction<Layer>, ActivationFunction) - Constructor for record class smile.vision.layer.Conv2dNormActivation.Options

Constructor.

Options(int, int, int, IntFunction<Layer>, ActivationFunction) - Constructor for record class smile.vision.layer.Conv2dNormActivation.Options

Constructor.

or(Tensor) - Method in class smile.deep.tensor.Tensor

Returns logical OR of two boolean tensors.

or(Predicate...) - Static method in class smile.plot.vega.Predicate

Logical OR composition to combine predicates.

or_(Tensor) - Method in class smile.deep.tensor.Tensor

Returns logical OR of two boolean tensors.

ORANGE - Static variable in interface smile.plot.swing.Palette

order - Variable in class smile.base.cart.CART

An index of training values.

order() - Method in record class smile.plot.vega.SortField

Returns the value of the order record component.

order(boolean) - Method in class smile.plot.vega.Mark

For line and trail marks, sets this order property false to make the lines use the original order in the data sources.

order(int) - Method in class smile.plot.vega.RegressionTransform

Sets the polynomial order (number of coefficients) for the "poly" method.

order(DataFrame) - Static method in class smile.base.cart.CART

Returns the index of ordered samples for each ordinal column.

ordinal - Variable in class smile.sequence.HMMLabeler

The lambda returns the ordinal numbers of symbols.

ordinal(int) - Static method in interface smile.util.Strings

Returns the string representation of ordinal number with suffix.

OrdinalNode - Class in smile.base.cart

A node with a ordinal split variable (real-valued or ordinal categorical value).

OrdinalNode(int, double, double, double, Node, Node) - Constructor for class smile.base.cart.OrdinalNode

Constructor.

OrdinalScale - Class in smile.data.measure

The ordinal type allows for rank order (1st, 2nd, 3rd, etc.) by which data can be sorted, but still does not allow for relative degree of difference between them.

OrdinalScale(int[], String[]) - Constructor for class smile.data.measure.OrdinalScale

Constructor.

OrdinalScale(Class<? extends Enum>) - Constructor for class smile.data.measure.OrdinalScale

Constructor.

OrdinalScale(String...) - Constructor for class smile.data.measure.OrdinalScale

Constructor.

OrdinalScale(List<String>) - Constructor for class smile.data.measure.OrdinalScale

Constructor.

OrdinalSplit - Class in smile.base.cart

The data about of a potential split for a leaf node.

OrdinalSplit(LeafNode, int, double, double, int, int, int, int, IntPredicate) - Constructor for class smile.base.cart.OrdinalSplit

Constructor.

orgqr(Layout, int, int, int, double[], int, double[]) - Method in interface smile.math.blas.LAPACK

Generates the real orthogonal matrix Q of the QR factorization formed by geqrf.

orgqr(Layout, int, int, int, double[], int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS

orgqr(Layout, int, int, int, float[], int, float[]) - Method in interface smile.math.blas.LAPACK

Generates the real orthogonal matrix Q of the QR factorization formed by geqrf.

orgqr(Layout, int, int, int, float[], int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS

orgqr(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer) - Method in interface smile.math.blas.LAPACK

Generates the real orthogonal matrix Q of the QR factorization formed by geqrf.

orgqr(Layout, int, int, int, DoubleBuffer, int, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

orgqr(Layout, int, int, int, FloatBuffer, int, FloatBuffer) - Method in interface smile.math.blas.LAPACK

Generates the real orthogonal matrix Q of the QR factorization formed by geqrf.

orgqr(Layout, int, int, int, FloatBuffer, int, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

orgqr(Layout, int, int, int, DoublePointer, int, DoublePointer) - Method in interface smile.math.blas.LAPACK

Generates the real orthogonal matrix Q of the QR factorization formed by geqrf.

orgqr(Layout, int, int, int, DoublePointer, int, DoublePointer) - Method in class smile.math.blas.openblas.OpenBLAS

orient(String) - Method in class smile.plot.vega.Axis

Sets the orientation of the axis.

orient(String) - Method in class smile.plot.vega.Legend

Sets the orientation of the legend.

orient(String) - Method in class smile.plot.vega.Mark

Sets the orientation of a non-stacked bar, tick, area, and line charts.

ormqr(Layout, Side, Transpose, int, int, int, double[], int, double[], double[], int) - Method in interface smile.math.blas.LAPACK

Overwrites the general real M-by-N matrix C with

ormqr(Layout, Side, Transpose, int, int, int, double[], int, double[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

ormqr(Layout, Side, Transpose, int, int, int, float[], int, float[], float[], int) - Method in interface smile.math.blas.LAPACK

Overwrites the general real M-by-N matrix C with

ormqr(Layout, Side, Transpose, int, int, int, float[], int, float[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

ormqr(Layout, Side, Transpose, int, int, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Overwrites the general real M-by-N matrix C with

ormqr(Layout, Side, Transpose, int, int, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

ormqr(Layout, Side, Transpose, int, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Overwrites the general real M-by-N matrix C with

ormqr(Layout, Side, Transpose, int, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

ormqr(Layout, Side, Transpose, int, int, int, DoublePointer, int, DoublePointer, DoublePointer, int) - Method in interface smile.math.blas.LAPACK

Overwrites the general real M-by-N matrix C with

ormqr(Layout, Side, Transpose, int, int, int, DoublePointer, int, DoublePointer, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

out() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns the value of the out record component.

outerRadius(double) - Method in class smile.plot.vega.Mark

Sets the primary (inner) radius in pixels for arc mark.

OUTLIER - Static variable in class smile.clustering.PartitionClustering

Cluster label for outliers or noises.

OUTLIER - Static variable in interface smile.vq.VectorQuantizer

The label for outliers or noises.

output - Variable in class smile.base.mlp.Layer

The output vector.

output - Variable in class smile.base.mlp.MultilayerPerceptron

The output layer.

output() - Method in class smile.base.cart.DecisionNode

Returns the predicted value.

output() - Method in class smile.base.cart.RegressionNode

Returns the predicted value.

output() - Method in class smile.base.mlp.Layer

Returns the output vector.

output(int[], int[]) - Method in interface smile.base.cart.Loss

Calculate the node output.

outputChannels() - Method in record class smile.vision.layer.MBConvConfig

Returns the value of the outputChannels record component.

OutputFunction - Enum Class in smile.base.mlp

The output function of neural networks.

outputGradient - Variable in class smile.base.mlp.Layer

The output gradient.

OutputLayer - Class in smile.base.mlp

The output layer in the neural network.

OutputLayer(int, int, OutputFunction, Cost) - Constructor for class smile.base.mlp.OutputLayer

Constructor.

OutputLayerBuilder - Class in smile.base.mlp

The builder of output layers.

OutputLayerBuilder(int, OutputFunction, Cost) - Constructor for class smile.base.mlp.OutputLayerBuilder

Constructor.

OVERWRITE - Enum constant in enum class smile.math.blas.SVDJob

The first min(m, n) singular vectors are overwritten on the matrix A.

P

p - Variable in class smile.base.mlp.Layer

The number of input variables.

p - Variable in class smile.base.mlp.MultilayerPerceptron

The dimensionality of input data.

p - Variable in class smile.stat.distribution.BernoulliDistribution

Probability of success.

p - Variable in class smile.stat.distribution.BinomialDistribution

The probability of success.

p - Variable in class smile.stat.distribution.EmpiricalDistribution

The probabilities for each x.

p - Variable in class smile.stat.distribution.GeometricDistribution

Probability of success on each trial.

p - Variable in class smile.stat.distribution.NegativeBinomialDistribution

The success probability in each experiment.

p - Variable in class smile.stat.distribution.ShiftedGeometricDistribution

The probability of success.

p - Variable in class smile.stat.GoodTuring

The probabilities corresponding to the observed frequencies.

p() - Method in class smile.timeseries.AR

Returns the order of AR.

p() - Method in class smile.timeseries.ARMA

Returns the order of AR.

p(double) - Method in class smile.stat.distribution.BetaDistribution

p(double) - Method in class smile.stat.distribution.ChiSquareDistribution

p(double) - Method in class smile.stat.distribution.DiscreteDistribution

p(double) - Method in interface smile.stat.distribution.Distribution

The probability density function for continuous distribution or probability mass function for discrete distribution at x.

p(double) - Method in class smile.stat.distribution.ExponentialDistribution

p(double) - Method in class smile.stat.distribution.FDistribution

p(double) - Method in class smile.stat.distribution.GammaDistribution

p(double) - Method in class smile.stat.distribution.GaussianDistribution

p(double) - Method in class smile.stat.distribution.KernelDensity

p(double) - Method in class smile.stat.distribution.LogisticDistribution

p(double) - Method in class smile.stat.distribution.LogNormalDistribution

p(double) - Method in class smile.stat.distribution.Mixture

p(double) - Method in class smile.stat.distribution.TDistribution

p(double) - Method in class smile.stat.distribution.WeibullDistribution

p(double[]) - Method in interface smile.stat.distribution.MultivariateDistribution

The probability density function for continuous distribution or probability mass function for discrete distribution at x.

p(double[]) - Method in class smile.stat.distribution.MultivariateGaussianDistribution

p(double[]) - Method in class smile.stat.distribution.MultivariateMixture

p(int) - Method in class smile.stat.distribution.BernoulliDistribution

p(int) - Method in class smile.stat.distribution.BinomialDistribution

p(int) - Method in class smile.stat.distribution.DiscreteDistribution

The probability mass function.

p(int) - Method in class smile.stat.distribution.DiscreteMixture

p(int) - Method in class smile.stat.distribution.EmpiricalDistribution

p(int) - Method in class smile.stat.distribution.GeometricDistribution

p(int) - Method in class smile.stat.distribution.HyperGeometricDistribution

p(int) - Method in class smile.stat.distribution.NegativeBinomialDistribution

p(int) - Method in class smile.stat.distribution.PoissonDistribution

p(int) - Method in class smile.stat.distribution.ShiftedGeometricDistribution

p(int[]) - Method in class smile.sequence.HMM

Returns the probability of an observation sequence given this HMM.

p(int[], int[]) - Method in class smile.sequence.HMM

Returns the joint probability of an observation sequence along a state sequence given this HMM.

p(T[]) - Method in class smile.sequence.HMMLabeler

Returns the probability of an observation sequence.

p(T[], int[]) - Method in class smile.sequence.HMMLabeler

Returns the joint probability of an observation sequence along a state sequence.

p0 - Variable in class smile.stat.GoodTuring

The joint probability of all unobserved species.

pacf(double[], int) - Static method in interface smile.timeseries.TimeSeries

Partial autocorrelation function.

padAngle(double) - Method in class smile.plot.vega.Mark

Setsthe angular padding applied to sides of the arc in radians.

padding() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns the value of the padding record component.

padding(double) - Method in class smile.plot.vega.Legend

Sets the padding between the border and content of the legend group.

padding(int) - Method in class smile.plot.vega.Concat

padding(int) - Method in class smile.plot.vega.Config

Specifies padding for all sides.

padding(int) - Method in class smile.plot.vega.Facet

padding(int) - Method in class smile.plot.vega.Repeat

padding(int) - Method in class smile.plot.vega.VegaLite

Specifies padding for all sides.

padding(int) - Method in class smile.plot.vega.View

padding(int, int, int, int) - Method in class smile.plot.vega.Concat

padding(int, int, int, int) - Method in class smile.plot.vega.Config

Specifies padding for each side.

padding(int, int, int, int) - Method in class smile.plot.vega.Facet

padding(int, int, int, int) - Method in class smile.plot.vega.Repeat

padding(int, int, int, int) - Method in class smile.plot.vega.VegaLite

Specifies padding for each side.

padding(int, int, int, int) - Method in class smile.plot.vega.View

pageDown() - Method in class smile.swing.table.PageTableModel

Moves to next page and fire a data changed (all rows).

PageRank - Class in smile.math.matrix

PageRank is a link analysis algorithm and it assigns a numerical weighting to each element of a hyperlinked set of documents, such as the World Wide Web, with the purpose of "measuring" its relative importance within the set.

PageTableModel - Class in smile.swing.table

A table model that performs "paging" of its data.

PageTableModel() - Constructor for class smile.swing.table.PageTableModel

Default constructor.

PageTableModel(int) - Constructor for class smile.swing.table.PageTableModel

Constructor.

pageUp() - Method in class smile.swing.table.PageTableModel

Moves to previous page and fire a data changed (all rows).

paint(Graphics2D, int, int) - Method in class smile.plot.swing.Canvas

Paints the canvas.

paint(Graphics) - Method in class smile.plot.swing.Axis

Draw the axis.

paint(Graphics) - Method in class smile.plot.swing.Bar

paint(Graphics) - Method in class smile.plot.swing.BarPlot

paint(Graphics) - Method in class smile.plot.swing.BoxPlot

paint(Graphics) - Method in class smile.plot.swing.Contour

paint(Graphics) - Method in class smile.plot.swing.Dendrogram

paint(Graphics) - Method in class smile.plot.swing.Grid

paint(Graphics) - Method in class smile.plot.swing.Heatmap

paint(Graphics) - Method in class smile.plot.swing.Hexmap

paint(Graphics) - Method in class smile.plot.swing.Histogram3D

paint(Graphics) - Method in class smile.plot.swing.Isoline

Paint the contour line.

paint(Graphics) - Method in class smile.plot.swing.Label

paint(Graphics) - Method in class smile.plot.swing.Line

paint(Graphics) - Method in class smile.plot.swing.LinePlot

paint(Graphics) - Method in class smile.plot.swing.Point

paint(Graphics) - Method in class smile.plot.swing.QQPlot

paint(Graphics) - Method in class smile.plot.swing.ScatterPlot

paint(Graphics) - Method in class smile.plot.swing.ScreePlot

paint(Graphics) - Method in class smile.plot.swing.Shape

Draws the shape.

paint(Graphics) - Method in class smile.plot.swing.SparseMatrixPlot

paint(Graphics) - Method in class smile.plot.swing.Staircase

paint(Graphics) - Method in class smile.plot.swing.StaircasePlot

paint(Graphics) - Method in class smile.plot.swing.Surface

paint(Graphics) - Method in class smile.plot.swing.TextPlot

paint(Graphics) - Method in class smile.plot.swing.Wireframe

paintIcon(Component, Graphics, int, int) - Method in class smile.swing.AlphaIcon

Paints the wrapped icon with this AlphaIcon's transparency.

Palette - Interface in smile.plot.swing

Color palette generator.

panel() - Method in class smile.plot.swing.Canvas

Returns a Swing JPanel of the canvas.

ParagraphSplitter - Interface in smile.nlp.tokenizer

A paragraph splitter segments text into paragraphs.

parallels(double...) - Method in class smile.plot.vega.Projection

For conic projections, sets the two standard parallels that define the map layout.

param() - Method in record class smile.plot.vega.WindowTransformField

Returns the value of the param record component.

parameters - Variable in class smile.math.LevenbergMarquardt

The fitted parameters.

params(boolean) - Method in class smile.plot.vega.RegressionTransform

Sets if the transform should return the regression model parameters (one object per group), rather than trend line points.

parquet(String) - Static method in interface smile.io.Read

Reads an Apache Parquet file.

parquet(String, String...) - Method in class smile.data.SQL

Creates an in-memory table from parquet files.

parquet(String, Map<String, String>, String...) - Method in class smile.data.SQL

Creates an in-memory table from parquet files.

parquet(Path) - Static method in interface smile.io.Read

Reads an Apache Parquet file.

Parquet - Class in smile.io

Apache Parquet is a columnar storage format that supports nested data structures.

parseDoubleArray(String) - Static method in interface smile.util.Strings

Parses a double array in format '[1.0, 2.0, 3.0]'.

parseIntArray(String) - Static method in interface smile.util.Strings

Parses an integer array in format '[1, 2, 3]'.

parser() - Method in class smile.data.type.StructType

Returns the lambda functions that parse field values.

partition(double) - Method in class smile.clustering.HierarchicalClustering

Cuts a tree into several groups by specifying the cut height.

partition(int) - Method in class smile.clustering.HierarchicalClustering

Cuts a tree into several groups by specifying the desired number.

PartitionClustering - Class in smile.clustering

Partition clustering.

PartitionClustering(int, int[]) - Constructor for class smile.clustering.PartitionClustering

Constructor.

PASTEL_GREEN - Static variable in interface smile.plot.swing.Palette

path(double[]) - Method in class smile.anomaly.IsolationTree

Returns the path length from the root to the leaf node.

Paths - Interface in smile.util

Static methods that return a Path by converting a path string or URI.

pbtrf(Layout, UPLO, int, int, double[], int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite band matrix A.

pbtrf(Layout, UPLO, int, int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

pbtrf(Layout, UPLO, int, int, float[], int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite band matrix A.

pbtrf(Layout, UPLO, int, int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

pbtrf(Layout, UPLO, int, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite band matrix A.

pbtrf(Layout, UPLO, int, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

pbtrf(Layout, UPLO, int, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite band matrix A.

pbtrf(Layout, UPLO, int, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

pbtrs(Layout, UPLO, int, int, int, double[], int, double[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

pbtrs(Layout, UPLO, int, int, int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

pbtrs(Layout, UPLO, int, int, int, float[], int, float[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

pbtrs(Layout, UPLO, int, int, int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

pbtrs(Layout, UPLO, int, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

pbtrs(Layout, UPLO, int, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

pbtrs(Layout, UPLO, int, int, int, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

pbtrs(Layout, UPLO, int, int, int, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

PCA - Class in smile.feature.extraction

Principal component analysis.

PCA(double[], double[], Matrix, Matrix, String...) - Constructor for class smile.feature.extraction.PCA

Constructor.

pdist(double[][]) - Static method in class smile.math.MathEx

Returns the pairwise distance matrix of multiple vectors.

pdist(double[][], boolean) - Static method in class smile.math.MathEx

Returns the pairwise distance matrix of multiple vectors.

pdist(float[][]) - Static method in class smile.math.MathEx

Returns the pairwise distance matrix of multiple vectors.

pdist(float[][], boolean) - Static method in class smile.math.MathEx

Returns the pairwise distance matrix of multiple vectors.

pdist(int[][]) - Static method in class smile.math.MathEx

Returns the pairwise distance matrix of multiple binary sparse vectors.

pdist(int[][], boolean) - Static method in class smile.math.MathEx

Returns the pairwise distance matrix of multiple binary sparse vectors.

pdist(SparseArray[]) - Static method in class smile.math.MathEx

Returns the pairwise distance matrix of multiple vectors.

pdist(SparseArray[], boolean) - Static method in class smile.math.MathEx

Returns the pairwise distance matrix of multiple vectors.

pdist(T[], double[][], Distance<T>) - Static method in class smile.math.MathEx

Computes the pairwise distance matrix of multiple vectors.

pdot(double[][]) - Static method in class smile.math.MathEx

Returns the pairwise dot product matrix of double vectors.

pdot(float[][]) - Static method in class smile.math.MathEx

Returns the pairwise dot product matrix of float vectors.

pdot(int[][]) - Static method in class smile.math.MathEx

Returns the pairwise dot product matrix of binary sparse vectors.

pdot(SparseArray[]) - Static method in class smile.math.MathEx

Returns the pairwise dot product matrix of multiple vectors.

PDT - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Predeterminer.

pearson(double[], double[]) - Static method in class smile.stat.hypothesis.CorTest

Pearson correlation coefficient test.

PearsonKernel - Class in smile.math.kernel

Pearson VII universal kernel.

PearsonKernel(double, double) - Constructor for class smile.math.kernel.PearsonKernel

Constructor.

PearsonKernel(double, double, double, double) - Constructor for class smile.math.kernel.PearsonKernel

Constructor.

peek() - Method in class smile.sort.DoubleHeapSelect

Returns the k-th smallest value seen so far.

peek() - Method in class smile.sort.FloatHeapSelect

Returns the k-th smallest value seen so far.

peek() - Method in class smile.sort.HeapSelect

Returns the k-th smallest value seen so far.

peek() - Method in class smile.sort.IntHeapSelect

Returns the k-th smallest value seen so far.

PennTreebankPOS - Enum Class in smile.nlp.pos

The Penn Treebank Tag set.

PennTreebankTokenizer - Class in smile.nlp.tokenizer

A word tokenizer that tokenizes English sentences using the conventions used by the Penn Treebank.

Percent - Static variable in interface smile.data.measure.Measure

Percent.

PERCENT - Static variable in class smile.swing.table.NumberCellRenderer

PerfectHash - Class in smile.hash

A perfect hash of an array of strings to their index in the array.

PerfectHash(int[], String...) - Constructor for class smile.hash.PerfectHash

Constructor.

PerfectHash(String...) - Constructor for class smile.hash.PerfectHash

Constructor.

PerfectMap<T> - Class in smile.hash

Perfect hash based immutable map.

PerfectMap.Builder<T> - Class in smile.hash

The builder of perfect map.

permutate(double[]) - Static method in class smile.math.MathEx

Permutates an array.

permutate(double[]) - Method in class smile.math.Random

Permutates an array.

permutate(float[]) - Static method in class smile.math.MathEx

Permutates an array.

permutate(float[]) - Method in class smile.math.Random

Permutates an array.

permutate(int) - Static method in class smile.math.MathEx

Returns a permutation of (0, 1, 2, ..., n-1).

permutate(int) - Method in class smile.math.Random

Returns a permutation of (0, 1, 2, ..., n-1).

permutate(int[]) - Static method in class smile.math.MathEx

Permutates an array.

permutate(int[]) - Method in class smile.math.Random

Permutates an array.

permutate(Object[]) - Static method in class smile.math.MathEx

Permutates an array.

permutate(Object[]) - Method in class smile.math.Random

Permutates an array.

permute(long...) - Method in class smile.deep.tensor.Tensor

Returns a view of the original tensor input with its dimensions permuted.

phase() - Method in class smile.math.Complex

Returns the angle/phase/argument between -pi and pi.

PHONE_NUMBER - Static variable in interface smile.util.Regex

U.S.

PHONE_NUMBER_EXTENSION - Static variable in interface smile.util.Regex

U.S.

piecewise(int[], double[]) - Static method in interface smile.math.TimeFunction

Returns the piecewise constant learning rate.

piecewise(int[], TimeFunction...) - Static method in interface smile.math.TimeFunction

Returns the piecewise constant learning rate.

pierce(double[], int) - Static method in class smile.timeseries.BoxTest

Box-Pierce test.

PINK - Static variable in interface smile.plot.swing.Palette

pinv() - Method in class smile.math.matrix.BigMatrix.SVD

Returns the pseudo inverse.

pinv() - Method in class smile.math.matrix.fp32.Matrix.SVD

Returns the pseudo inverse.

pinv() - Method in class smile.math.matrix.Matrix.SVD

Returns the pseudo inverse.

pipeline(Transform...) - Static method in interface smile.data.transform.Transform

Returns a pipeline of data transforms.

pivot(String, String) - Method in class smile.plot.vega.Transform

Adds a pivot transform.

PivotTransform - Class in smile.plot.vega

The pivot transform maps unique values from a field to new aggregated fields (columns) in the output stream.

PlattScaling - Class in smile.classification

Platt scaling or Platt calibration is a way of transforming the outputs of a classification model into a probability distribution over classes.

PlattScaling(double, double) - Constructor for class smile.classification.PlattScaling

Constructor.

Plot - Class in smile.plot.swing

The abstract base class of plots.

Plot() - Constructor for class smile.plot.swing.Plot

Constructor.

Plot(Color) - Constructor for class smile.plot.swing.Plot

Constructor.

PlotGrid - Class in smile.plot.swing

PlotGrid organizes multiple plots in a grid layout.

PlotGrid(int, int) - Constructor for class smile.plot.swing.PlotGrid

Constructor.

PlotGrid(PlotPanel...) - Constructor for class smile.plot.swing.PlotGrid

Constructor.

PlotPanel - Class in smile.plot.swing

Canvas for mathematical plots.

PlotPanel(Canvas) - Constructor for class smile.plot.swing.PlotPanel

Constructor

PLUM - Static variable in interface smile.plot.swing.Palette

point(boolean) - Method in class smile.plot.vega.Mark

Sets whether overlaying points on top of line or area marks.

Point - Class in smile.plot.swing

One more more points in the plot.

Point(double[][], char, Color) - Constructor for class smile.plot.swing.Point

Constructor.

pointRadius(double) - Method in class smile.plot.vega.Projection

Sets the default radius (in pixels) to use when drawing GeoJSON Point and MultiPoint geometries.

points() - Method in class smile.neighbor.lsh.Bucket

Returns the points in the bucket.

Poisson - Interface in smile.glm.model

The response variable is of Poisson distribution.

PoissonDistribution - Class in smile.stat.distribution

Poisson distribution expresses the probability of a number of events occurring in a fixed period of time if these events occur with a known average rate and independently of the time since the last event.

PoissonDistribution(double) - Constructor for class smile.stat.distribution.PoissonDistribution

Constructor.

poll() - Method in class smile.util.PriorityQueue

Removes and returns the index of item with minimum value (highest priority).

POLYAURN - Enum constant in enum class smile.classification.DiscreteNaiveBayes.Model

The document Polya Urn model is similar to MULTINOMIAL but different in the conditional probability update during learning.

polynomial(double, double, double, double) - Static method in interface smile.math.TimeFunction

Returns the polynomial learning rate decay function that starts with an initial learning rate and reach an end learning rate in the given decay steps, without cycling.

polynomial(double, double, double, double, boolean) - Static method in interface smile.math.TimeFunction

Returns the polynomial learning rate decay function that starts with an initial learning rate and reach an end learning rate in the given decay steps.

Polynomial - Class in smile.math.kernel

The polynomial kernel.

Polynomial(int, double, double, double[], double[]) - Constructor for class smile.math.kernel.Polynomial

Constructor.

PolynomialKernel - Class in smile.math.kernel

The polynomial kernel.

PolynomialKernel(int) - Constructor for class smile.math.kernel.PolynomialKernel

Constructor with scale 1 and offset 0.

PolynomialKernel(int, double, double) - Constructor for class smile.math.kernel.PolynomialKernel

Constructor.

PolynomialKernel(int, double, double, double[], double[]) - Constructor for class smile.math.kernel.PolynomialKernel

Constructor.

population() - Method in class smile.gap.GeneticAlgorithm

Returns the population of current generation.

PorterStemmer - Class in smile.nlp.stemmer

Porter's stemming algorithm.

PorterStemmer() - Constructor for class smile.nlp.stemmer.PorterStemmer

Constructor.

POS - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Possessive ending.

position(double) - Method in class smile.plot.vega.Axis

Sets the anchor position of the axis in pixels.

PositionalEncoding - Class in smile.llm

Positional encoding injects some information about the relative or absolute position of the tokens in the sequence.

PositionalEncoding(int) - Constructor for class smile.llm.PositionalEncoding

Constructor.

PositionalEncoding(int, double, int) - Constructor for class smile.llm.PositionalEncoding

Constructor.

POSTagger - Interface in smile.nlp.pos

Part-of-speech tagging (POS tagging) is the process of marking up the words in a sentence as corresponding to a particular part of speech.

posteriori - Variable in class smile.validation.ClassificationValidation

The posteriori probability of prediction if the model is a soft classifier.

posteriori(double) - Method in class smile.stat.distribution.Mixture

Returns the posteriori probabilities.

posteriori(double[]) - Method in class smile.base.cart.DecisionNode

Returns the class probability.

posteriori(double[]) - Method in class smile.stat.distribution.MultivariateMixture

Returns the posteriori probabilities.

posteriori(int) - Method in class smile.stat.distribution.DiscreteMixture

Returns the posteriori probabilities.

posteriori(int[], double[]) - Static method in class smile.base.cart.DecisionNode

Returns the class probability.

PosterioriModel - Class in smile.neighbor.lsh

Pre-computed posteriori probabilities for generating multiple probes.

PosterioriModel(MultiProbeHash, MultiProbeSample[], int, double) - Constructor for class smile.neighbor.lsh.PosterioriModel

Constructor.

postprocess(double[]) - Method in class smile.feature.extraction.PCA

postprocess(double[]) - Method in class smile.feature.extraction.ProbabilisticPCA

postprocess(double[]) - Method in class smile.feature.extraction.Projection

Postprocess the output vector after projection.

posv(Layout, UPLO, int, int, double[], int, double[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

posv(Layout, UPLO, int, int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

posv(Layout, UPLO, int, int, float[], int, float[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

posv(Layout, UPLO, int, int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

posv(Layout, UPLO, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

posv(Layout, UPLO, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

posv(Layout, UPLO, int, int, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

posv(Layout, UPLO, int, int, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

potrf(Layout, UPLO, int, double[], int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite matrix A.

potrf(Layout, UPLO, int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

potrf(Layout, UPLO, int, float[], int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite matrix A.

potrf(Layout, UPLO, int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

potrf(Layout, UPLO, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite matrix A.

potrf(Layout, UPLO, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

potrf(Layout, UPLO, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite matrix A.

potrf(Layout, UPLO, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

potrf(Layout, UPLO, int, DoublePointer, int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite matrix A.

potrf(Layout, UPLO, int, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

potrf2(Layout, UPLO, int, double[], int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite matrix A using the recursive algorithm.

potrf2(Layout, UPLO, int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

potrf2(Layout, UPLO, int, float[], int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite matrix A using the recursive algorithm.

potrf2(Layout, UPLO, int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

potrf2(Layout, UPLO, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite matrix A using the recursive algorithm.

potrf2(Layout, UPLO, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

potrf2(Layout, UPLO, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite matrix A using the recursive algorithm.

potrf2(Layout, UPLO, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

potrs(Layout, UPLO, int, int, double[], int, double[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

potrs(Layout, UPLO, int, int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

potrs(Layout, UPLO, int, int, float[], int, float[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

potrs(Layout, UPLO, int, int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

potrs(Layout, UPLO, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

potrs(Layout, UPLO, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

potrs(Layout, UPLO, int, int, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

potrs(Layout, UPLO, int, int, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

potrs(Layout, UPLO, int, int, DoublePointer, int, DoublePointer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

potrs(Layout, UPLO, int, int, DoublePointer, int, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

POUND - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Punctuation #

pow(double[], double) - Static method in class smile.math.MathEx

Raise each element of an array to a scalar power.

pow2(double) - Static method in class smile.math.MathEx

Returns x * x.

PowerVariogram - Class in smile.interpolation.variogram

Power variogram.

PowerVariogram(double[][], double[]) - Constructor for class smile.interpolation.variogram.PowerVariogram

Constructor.

PowerVariogram(double[][], double[], double) - Constructor for class smile.interpolation.variogram.PowerVariogram

Constructor.

PowerVariogram(double[][], double[], double, double) - Constructor for class smile.interpolation.variogram.PowerVariogram

Constructor.

ppsv(Layout, UPLO, int, int, double[], double[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

ppsv(Layout, UPLO, int, int, double[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

ppsv(Layout, UPLO, int, int, float[], float[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

ppsv(Layout, UPLO, int, int, float[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

ppsv(Layout, UPLO, int, int, DoubleBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

ppsv(Layout, UPLO, int, int, DoubleBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

ppsv(Layout, UPLO, int, int, FloatBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

ppsv(Layout, UPLO, int, int, FloatBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

pptrf(Layout, UPLO, int, double[]) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite packed matrix A.

pptrf(Layout, UPLO, int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS

pptrf(Layout, UPLO, int, float[]) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite packed matrix A.

pptrf(Layout, UPLO, int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS

pptrf(Layout, UPLO, int, DoubleBuffer) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite packed matrix A.

pptrf(Layout, UPLO, int, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

pptrf(Layout, UPLO, int, FloatBuffer) - Method in interface smile.math.blas.LAPACK

Computes the Cholesky factorization of a real symmetric positive definite packed matrix A.

pptrf(Layout, UPLO, int, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

pptrs(Layout, UPLO, int, int, double[], double[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

pptrs(Layout, UPLO, int, int, double[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

pptrs(Layout, UPLO, int, int, float[], float[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

pptrs(Layout, UPLO, int, int, float[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

pptrs(Layout, UPLO, int, int, DoubleBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

pptrs(Layout, UPLO, int, int, DoubleBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

pptrs(Layout, UPLO, int, int, FloatBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

pptrs(Layout, UPLO, int, int, FloatBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

pr - Variable in class smile.neighbor.lsh.PrH

The probability.

precision - Variable in class smile.validation.ClassificationMetrics

The precision on validation data.

precision(double) - Method in class smile.plot.vega.Projection

Sets the threshold for the projection's adaptive resampling to the specified value in pixels.

Precision - Class in smile.deep.metric

The precision or positive predictive value (PPV) is ratio of true positives to combined true and false positives, which is different from sensitivity.

Precision - Class in smile.validation.metric

The precision or positive predictive value (PPV) is ratio of true positives to combined true and false positives, which is different from sensitivity.

Precision() - Constructor for class smile.deep.metric.Precision

Constructor.

Precision() - Constructor for class smile.validation.metric.Precision

Precision(double) - Constructor for class smile.deep.metric.Precision

Constructor.

Precision(Averaging) - Constructor for class smile.deep.metric.Precision

Constructor.

predicate() - Method in class smile.base.cart.NominalSplit

predicate() - Method in class smile.base.cart.OrdinalSplit

predicate() - Method in class smile.base.cart.Split

Returns the lambda that tests on the split feature.

Predicate - Class in smile.plot.vega

To test a data point in a filter transform or a test property in conditional encoding, a predicate definition of the following forms must be specified: - a Vega expression string, where datum can be used to refer to the current data object.

Predicate(String) - Constructor for class smile.plot.vega.Predicate

Constructor.

Predicate(String, boolean) - Constructor for class smile.plot.vega.Predicate

Constructor of parameter predicate.

predict(double) - Method in class smile.classification.IsotonicRegressionScaling

Returns the posterior probability estimate P(y = 1 | x).

predict(double[]) - Method in class smile.classification.FLD

predict(double[]) - Method in class smile.classification.LDA

predict(double[]) - Method in class smile.classification.LogisticRegression.Binomial

predict(double[]) - Method in class smile.classification.LogisticRegression.Multinomial

predict(double[]) - Method in class smile.classification.MLP

predict(double[]) - Method in class smile.classification.NaiveBayes

Predict the class of an instance.

predict(double[]) - Method in class smile.classification.QDA

predict(double[]) - Method in class smile.clustering.DENCLUE

Classifies a new observation.

predict(double[]) - Method in class smile.regression.LinearModel

Predicts the dependent variable of an instance.

predict(double[]) - Method in class smile.regression.MLP

predict(double[], double[]) - Method in class smile.classification.LDA

predict(double[], double[]) - Method in class smile.classification.LogisticRegression.Binomial

predict(double[], double[]) - Method in class smile.classification.LogisticRegression.Multinomial

predict(double[], double[]) - Method in class smile.classification.MLP

predict(double[], double[]) - Method in class smile.classification.NaiveBayes

Predict the class of an instance.

predict(double[], double[]) - Method in class smile.classification.QDA

predict(int[]) - Method in class smile.classification.DiscreteNaiveBayes

Predict the class of an instance.

predict(int[]) - Method in class smile.classification.Maxent.Binomial

predict(int[]) - Method in class smile.classification.Maxent.Multinomial

predict(int[]) - Method in class smile.sequence.HMM

Returns the most likely state sequence given the observation sequence by the Viterbi algorithm, which maximizes the probability of P(I | O, HMM).

predict(int[], double[]) - Method in class smile.classification.DiscreteNaiveBayes

Predict the class of an instance.

predict(int[], double[]) - Method in class smile.classification.Maxent.Binomial

predict(int[], double[]) - Method in class smile.classification.Maxent.Multinomial

predict(List<T>) - Method in interface smile.classification.Classifier

Predicts the class labels of a list of instances.

predict(List<T>) - Method in interface smile.regression.Regression

Predicts the dependent variable of a list of instances.

predict(List<T>, List<double[]>) - Method in interface smile.classification.Classifier

Predicts the class labels of a list of instances.

predict(DataFrame) - Method in interface smile.classification.DataFrameClassifier

Predicts the class labels of a data frame.

predict(DataFrame) - Method in class smile.glm.GLM

Predicts the mean response.

predict(DataFrame) - Method in interface smile.regression.DataFrameRegression

Predicts the dependent variables of a data frame.

predict(DataFrame) - Method in class smile.regression.LinearModel

predict(DataFrame, List<double[]>) - Method in interface smile.classification.DataFrameClassifier

Predicts the class labels of a dataset.

predict(Dataset<T, ?>) - Method in interface smile.classification.Classifier

Predicts the class labels of a dataset.

predict(Dataset<T, ?>) - Method in interface smile.regression.Regression

Predicts the dependent variable of a dataset.

predict(Dataset<T, ?>, List<double[]>) - Method in interface smile.classification.Classifier

Predicts the class labels of a dataset.

predict(Tuple) - Method in class smile.base.cart.InternalNode

predict(Tuple) - Method in class smile.base.cart.LeafNode

predict(Tuple) - Method in interface smile.base.cart.Node

Evaluate the tree over an instance.

predict(Tuple) - Method in class smile.base.cart.NominalNode

predict(Tuple) - Method in class smile.base.cart.OrdinalNode

predict(Tuple) - Method in class smile.classification.AdaBoost

predict(Tuple) - Method in class smile.classification.DecisionTree

predict(Tuple) - Method in class smile.classification.GradientTreeBoost

predict(Tuple) - Method in class smile.classification.RandomForest

predict(Tuple) - Method in class smile.glm.GLM

Predicts the mean response.

predict(Tuple) - Method in class smile.regression.GradientTreeBoost

predict(Tuple) - Method in class smile.regression.LinearModel

predict(Tuple) - Method in class smile.regression.RandomForest

predict(Tuple) - Method in class smile.regression.RegressionTree

predict(Tuple[]) - Method in class smile.sequence.CRF

Returns the most likely label sequence given the feature sequence by the forward-backward algorithm.

predict(Tuple, double[]) - Method in class smile.classification.AdaBoost

Predicts the class label of an instance and also calculate a posteriori probabilities.

predict(Tuple, double[]) - Method in class smile.classification.DecisionTree

Predicts the class label of an instance and also calculate a posteriori probabilities.

predict(Tuple, double[]) - Method in class smile.classification.GradientTreeBoost

predict(Tuple, double[]) - Method in class smile.classification.RandomForest

predict(SparseArray) - Method in class smile.classification.DiscreteNaiveBayes

Predict the class of an instance.

predict(SparseArray) - Method in class smile.classification.SparseLogisticRegression.Binomial

predict(SparseArray) - Method in class smile.classification.SparseLogisticRegression.Multinomial

predict(SparseArray, double[]) - Method in class smile.classification.DiscreteNaiveBayes

Predict the class of an instance.

predict(SparseArray, double[]) - Method in class smile.classification.SparseLogisticRegression.Binomial

predict(SparseArray, double[]) - Method in class smile.classification.SparseLogisticRegression.Multinomial

predict(T) - Method in interface smile.classification.Classifier

Predicts the class label of an instance.

predict(T) - Method in class smile.classification.KNN

predict(T) - Method in class smile.classification.OneVersusOne

Prediction is based on voting.

predict(T) - Method in class smile.classification.OneVersusRest

predict(T) - Method in class smile.classification.RBFNetwork

predict(T) - Method in class smile.classification.SVM

predict(T) - Method in class smile.clustering.DBSCAN

Classifies a new observation.

predict(T) - Method in class smile.clustering.MEC

Cluster a new instance.

predict(T) - Method in class smile.regression.GaussianProcessRegression

predict(T) - Method in class smile.regression.KernelMachine

predict(T) - Method in class smile.regression.RBFNetwork

predict(T) - Method in interface smile.regression.Regression

Predicts the dependent variable of an instance.

predict(T[]) - Method in interface smile.classification.Classifier

Predicts the class labels of an array of instances.

predict(T[]) - Method in interface smile.regression.Regression

Predicts the dependent variable of an array of instances.

predict(T[]) - Method in class smile.sequence.CRFLabeler

Returns the most likely label sequence given the feature sequence by the forward-backward algorithm.

predict(T[]) - Method in class smile.sequence.HMMLabeler

Returns the most likely state sequence given the observation sequence by the Viterbi algorithm, which maximizes the probability of P(I | O, HMM).

predict(T[]) - Method in interface smile.sequence.SequenceLabeler

Predicts the sequence labels.

predict(T[], double[][]) - Method in interface smile.classification.Classifier

Predicts the class labels of an array of instances.

predict(T, double[]) - Method in interface smile.classification.Classifier

Predicts the class label of an instance and also calculate a posteriori probabilities.

predict(T, double[]) - Method in class smile.classification.KNN

predict(T, double[]) - Method in class smile.classification.OneVersusOne

Prediction is based posteriori probability estimation.

predict(T, double[]) - Method in class smile.classification.OneVersusRest

predict(T, double[]) - Method in class smile.regression.GaussianProcessRegression

Predicts the mean and standard deviation of an instance.

predict(U) - Method in class smile.clustering.CentroidClustering

Classifies a new observation.

prediction - Variable in class smile.validation.ClassificationValidation

The model prediction.

prediction - Variable in class smile.validation.RegressionValidation

The model prediction.

predictors() - Method in class smile.data.formula.Formula

Returns the predictors.

predictors(Tuple) - Method in class smile.base.cart.CART

Returns the predictors by the model formula if it is not null.

preferredDevice() - Static method in class smile.deep.tensor.Device

Returns the preferred (most powerful) device.

preprocess(double[]) - Method in class smile.feature.extraction.Projection

Preprocess the input vector before projection.

prh - Variable in class smile.neighbor.lsh.PrZ

The n_i probabilities for h_m hash function, where n_i = u_{i_max} - u_{i_min} + 1.

PrH - Class in smile.neighbor.lsh

The probability for given query object and hash function.

PrH(int, double) - Constructor for class smile.neighbor.lsh.PrH

Constructor.

print() - Method in class smile.deep.tensor.Tensor

Prints the tensor on the standard output.

print() - Method in class smile.plot.swing.PlotGrid

Prints the plot.

print() - Method in class smile.plot.swing.PlotPanel

Prints the plot.

print(Graphics, PageFormat, int) - Method in class smile.plot.swing.PlotGrid

print(Printable) - Method in class smile.swing.Printer

Prints a document that implements Printable interface.

Printer - Class in smile.swing

A printer controller object.

priori - Variable in class smile.classification.ClassLabels

The estimated priori probabilities.

priori - Variable in class smile.stat.distribution.DiscreteMixture.Component

The priori probability of component.

priori - Variable in class smile.stat.distribution.Mixture.Component

The priori probability of component.

priori - Variable in class smile.stat.distribution.MultivariateMixture.Component

The priori probability of component.

priori() - Method in class smile.classification.DiscreteNaiveBayes

Returns a priori probabilities.

priori() - Method in class smile.classification.LDA

Returns a priori probabilities.

priori() - Method in class smile.classification.NaiveBayes

Returns a priori probabilities.

priori() - Method in class smile.classification.QDA

Returns a priori probabilities.

PriorityQueue - Class in smile.util

Priority Queue for index items.

PriorityQueue(double[]) - Constructor for class smile.util.PriorityQueue

Constructor.

PriorityQueue(int, double[]) - Constructor for class smile.util.PriorityQueue

Constructor.

ProbabilisticClassificationMetric - Interface in smile.validation.metric

An abstract interface to measure the probabilistic classification performance.

ProbabilisticPCA - Class in smile.feature.extraction

Probabilistic principal component analysis.

ProbabilisticPCA(double, double[], Matrix, Matrix, String...) - Constructor for class smile.feature.extraction.ProbabilisticPCA

Constructor.

probablePrime(long, int) - Static method in class smile.math.MathEx

Returns a probably prime number greater than n.

Probe - Class in smile.neighbor.lsh

Probe to check for nearest neighbors.

Probe(int[]) - Constructor for class smile.neighbor.lsh.Probe

Constructor.

probs(double[]) - Method in class smile.plot.vega.QuantileTransform

Sets an array of probabilities in the range (0, 1) for which to compute quantile values.

ProductKernel<T> - Class in smile.math.kernel

The product kernel takes two kernels and combines them via k1(x, y) * k2(x, y).

ProductKernel(MercerKernel<T>, MercerKernel<T>) - Constructor for class smile.math.kernel.ProductKernel

Constructor.

project(double[]) - Method in class smile.classification.FLD

Projects a sample to the feature space.

project(double[][]) - Method in class smile.classification.FLD

Projects samples to the feature space.

projection - Variable in class smile.feature.extraction.Projection

The projection matrix.

projection() - Method in class smile.manifold.KPCA

Returns the projection matrix.

projection(String) - Method in class smile.plot.vega.View

Returns the defining properties of geographic projection, which will be applied to shape path for "geoshape" marks and to latitude and "longitude" channels for other marks.

Projection - Class in smile.feature.extraction

A projection is a kind of feature extraction technique that transforms data from the input space to a feature space, linearly or non-linearly.

Projection - Class in smile.plot.vega

The geographic projection, which will be applied to shape path for "geoshape" marks and to latitude and "longitude" channels for other marks.

Projection(Matrix, String, String...) - Constructor for class smile.feature.extraction.Projection

Constructor.

prompt(DataType, DataType) - Static method in interface smile.data.type.DataType

Type promotion when apply to expressions.

propagate(double[]) - Method in class smile.base.mlp.InputLayer

propagate(double[]) - Method in class smile.base.mlp.Layer

Propagates the signals from a lower layer to this layer.

propagate(double[], boolean) - Method in class smile.base.mlp.MultilayerPerceptron

Propagates the signals through the neural network.

propagateDropout() - Method in class smile.base.mlp.Layer

Propagates the output signals through the implicit dropout layer.

propertyChange(PropertyChangeEvent) - Method in class smile.swing.Table.RowHeader

proportion - Variable in class smile.manifold.MDS

The proportion of variance contained in each principal component.

proximity(double[][]) - Static method in class smile.clustering.linkage.Linkage

Computes the proximity matrix (linearized in column major) based on Euclidean distance.

proximity(T[], Distance<T>) - Static method in class smile.clustering.linkage.Linkage

Computes the proximity matrix (linearized in column major).

PRP - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Personal pronoun.

PRP$ - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Possessive pronoun.

prune(DataFrame) - Method in class smile.classification.DecisionTree

Returns a new decision tree by reduced error pruning.

prune(DataFrame) - Method in class smile.classification.RandomForest

Returns a new random forest by reduced error pruning.

PrZ - Class in smile.neighbor.lsh

The probability list of all buckets for given query object.

PrZ(int, PrH[]) - Constructor for class smile.neighbor.lsh.PrZ

Constructor.

Punctuations - Interface in smile.nlp.dictionary

Punctuation marks are symbols that indicate the structure and organization of written language, as well as intonation and pauses to be observed when reading aloud.

PURPLE - Static variable in interface smile.plot.swing.Palette

pushRelabel(double[][], int, int) - Method in class smile.graph.AdjacencyMatrix

Push-relabel algorithm for maximum flow.

put(double[], E) - Method in class smile.neighbor.LSH

Insert an item into the hash table.

put(double[], E) - Method in class smile.neighbor.MutableLSH

put(int, double) - Method in class smile.util.IntDoubleHashMap

Associates the specified value with the specified key in this map.

put(K[], V) - Method in class smile.nlp.Trie

Add a key with associated value to the trie.

put(K, V) - Method in class smile.neighbor.SNLSH

Adds a new item.

put(Tensor, Index...) - Method in class smile.deep.tensor.Tensor

Updates a portion of tensor.

put(Tensor, Tensor) - Method in class smile.deep.tensor.Tensor

Updates a portion of tensor.

put_(byte, int...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(byte, long...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(double, int...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(double, long...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(float, int...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(float, long...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(int, int...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(int, long...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(long, int...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(long, long...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(short, int...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(short, long...) - Method in class smile.deep.tensor.Tensor

Updates an element in place.

put_(Tensor, Index...) - Method in class smile.deep.tensor.Tensor

Updates a portion of tensor in place.

put_(Tensor, Tensor) - Method in class smile.deep.tensor.Tensor

Updates a portion of tensor in place.

pvalue - Variable in class smile.stat.hypothesis.ChiSqTest

p-value

pvalue - Variable in class smile.stat.hypothesis.CorTest

Two-sided p-value.

pvalue - Variable in class smile.stat.hypothesis.FTest

p-value.

pvalue - Variable in class smile.stat.hypothesis.KSTest

P-value.

pvalue - Variable in class smile.stat.hypothesis.TTest

p-value.

pvalue - Variable in class smile.timeseries.BoxTest

p-value

pvalue() - Method in class smile.regression.LinearModel

Returns the p-value of goodness-of-fit test.

Q

q - Variable in class smile.stat.distribution.BernoulliDistribution

Probability of failure.

q - Variable in class smile.timeseries.BoxTest

Box-Pierce or Ljung-Box statistic.

q() - Method in class smile.timeseries.ARMA

Returns the order of MA.

Q() - Method in class smile.math.matrix.BigMatrix.QR

Returns the orthogonal factor.

Q() - Method in class smile.math.matrix.fp32.Matrix.QR

Returns the orthogonal factor.

Q() - Method in class smile.math.matrix.Matrix.QR

Returns the orthogonal factor.

q1(double[]) - Static method in class smile.math.MathEx

Find the first quantile (p = 1/4) of an array of type double.

q1(double[]) - Static method in interface smile.sort.QuickSelect

Find the first quantile (p = 1/4) of an array of type double.

q1(float[]) - Static method in class smile.math.MathEx

Find the first quantile (p = 1/4) of an array of type float.

q1(float[]) - Static method in interface smile.sort.QuickSelect

Find the first quantile (p = 1/4) of an array of type float.

q1(int[]) - Static method in class smile.math.MathEx

Find the first quantile (p = 1/4) of an array of type int.

q1(int[]) - Static method in interface smile.sort.QuickSelect

Find the first quantile (p = 1/4) of an array of type integer.

q1(T[]) - Static method in class smile.math.MathEx

Find the first quantile (p = 1/4) of an array of type double.

q1(T[]) - Static method in interface smile.sort.QuickSelect

Find the first quantile (p = 1/4) of an array of type double.

q3(double[]) - Static method in class smile.math.MathEx

Find the third quantile (p = 3/4) of an array of type double.

q3(double[]) - Static method in interface smile.sort.QuickSelect

Find the third quantile (p = 3/4) of an array of type double.

q3(float[]) - Static method in class smile.math.MathEx

Find the third quantile (p = 3/4) of an array of type float.

q3(float[]) - Static method in interface smile.sort.QuickSelect

Find the third quantile (p = 3/4) of an array of type float.

q3(int[]) - Static method in class smile.math.MathEx

Find the third quantile (p = 3/4) of an array of type int.

q3(int[]) - Static method in interface smile.sort.QuickSelect

Find the third quantile (p = 3/4) of an array of type integer.

q3(T[]) - Static method in class smile.math.MathEx

Find the third quantile (p = 3/4) of an array of type double.

q3(T[]) - Static method in interface smile.sort.QuickSelect

Find the third quantile (p = 3/4) of an array of type double.

QDA - Class in smile.classification

Quadratic discriminant analysis.

QDA(double[], double[][], double[][], Matrix[]) - Constructor for class smile.classification.QDA

Constructor.

QDA(double[], double[][], double[][], Matrix[], IntSet) - Constructor for class smile.classification.QDA

Constructor.

QInt8 - Enum constant in enum class smile.deep.tensor.ScalarType

8-bit quantized signed tensor type which represents a compressed floating point tensor.

QQPlot - Class in smile.plot.swing

A Q-Q plot ("Q" stands for quantile) is a probability plot, a kind of graphical method for comparing two probability distributions, by plotting their quantiles against each other.

QQPlot(double[][]) - Constructor for class smile.plot.swing.QQPlot

Constructor.

qr - Variable in class smile.math.matrix.BigMatrix.QR

The QR decomposition.

qr - Variable in class smile.math.matrix.fp32.Matrix.QR

The QR decomposition.

qr - Variable in class smile.math.matrix.Matrix.QR

The QR decomposition.

qr() - Method in class smile.math.matrix.BigMatrix

QR Decomposition.

qr() - Method in class smile.math.matrix.fp32.Matrix

QR Decomposition.

qr() - Method in class smile.math.matrix.Matrix

QR Decomposition.

qr(boolean) - Method in class smile.math.matrix.BigMatrix

QR Decomposition.

qr(boolean) - Method in class smile.math.matrix.fp32.Matrix

QR Decomposition.

qr(boolean) - Method in class smile.math.matrix.Matrix

QR Decomposition.

QR(BigMatrix, DoublePointer) - Constructor for class smile.math.matrix.BigMatrix.QR

Constructor.

QR(Matrix, float[]) - Constructor for class smile.math.matrix.fp32.Matrix.QR

Constructor.

QR(Matrix, double[]) - Constructor for class smile.math.matrix.Matrix.QR

Constructor.

quantile(double) - Static method in interface smile.base.cart.Loss

Quantile regression loss.

quantile(double) - Method in class smile.sort.IQAgent

Returns the estimated p-quantile for the data seen so far.

quantile(double) - Method in class smile.stat.distribution.BernoulliDistribution

quantile(double) - Method in class smile.stat.distribution.BetaDistribution

quantile(double) - Method in class smile.stat.distribution.BinomialDistribution

quantile(double) - Method in class smile.stat.distribution.ChiSquareDistribution

quantile(double) - Method in class smile.stat.distribution.DiscreteMixture

quantile(double) - Method in interface smile.stat.distribution.Distribution

The quantile, the probability to the left of quantile is p.

quantile(double) - Method in class smile.stat.distribution.EmpiricalDistribution

quantile(double) - Method in class smile.stat.distribution.ExponentialDistribution

quantile(double) - Method in class smile.stat.distribution.FDistribution

quantile(double) - Method in class smile.stat.distribution.GammaDistribution

quantile(double) - Method in class smile.stat.distribution.GaussianDistribution

The quantile, the probability to the left of quantile(p) is p.

quantile(double) - Method in class smile.stat.distribution.GeometricDistribution

quantile(double) - Method in class smile.stat.distribution.HyperGeometricDistribution

quantile(double) - Method in class smile.stat.distribution.KernelDensity

Inverse of CDF.

quantile(double) - Method in class smile.stat.distribution.LogisticDistribution

quantile(double) - Method in class smile.stat.distribution.LogNormalDistribution

quantile(double) - Method in class smile.stat.distribution.Mixture

quantile(double) - Method in class smile.stat.distribution.NegativeBinomialDistribution

quantile(double) - Method in class smile.stat.distribution.PoissonDistribution

quantile(double) - Method in class smile.stat.distribution.ShiftedGeometricDistribution

quantile(double) - Method in class smile.stat.distribution.TDistribution

quantile(double) - Method in class smile.stat.distribution.WeibullDistribution

quantile(double, double, double) - Method in interface smile.stat.distribution.Distribution

Inversion of CDF by bisection numeric root finding of "cdf(x) = p" for continuous distribution.

quantile(double, double, double, double) - Method in interface smile.stat.distribution.Distribution

Inversion of CDF by bisection numeric root finding of "cdf(x) = p" for continuous distribution.

quantile(double, int, int) - Method in class smile.stat.distribution.DiscreteDistribution

Inversion of cdf by bisection numeric root finding of cdf(x) = p for discrete distribution.

quantile(String) - Method in class smile.plot.vega.Transform

Adds a quantile transform.

Quantile - Enum constant in enum class smile.base.cart.Loss.Type

Quantile regression.

quantile2tailed(double) - Method in class smile.stat.distribution.TDistribution

Two-tailed quantile.

QuantileTransform - Class in smile.plot.vega

The quantile transform calculates empirical quantile values for an input data stream.

quantize(double[]) - Method in class smile.vq.BIRCH

quantize(double[]) - Method in class smile.vq.GrowingNeuralGas

quantize(double[]) - Method in class smile.vq.NeuralGas

quantize(double[]) - Method in class smile.vq.NeuralMap

quantize(double[]) - Method in class smile.vq.SOM

quantize(double[]) - Method in interface smile.vq.VectorQuantizer

Quantize a new observation.

QUARTER - Enum constant in enum class smile.data.formula.DateFeature

The quarter-of-year has values from 1 to 4.

query - Variable in class smile.neighbor.lsh.MultiProbeSample

The query object.

query(String) - Method in class smile.data.SQL

Executes a SELECT statement.

query(T[]) - Method in class smile.regression.GaussianProcessRegression

Evaluates the Gaussian Process at some query points.

QuickSelect - Interface in smile.sort

Selection is asking for the k-th smallest element out of n elements.

QuickSort - Class in smile.sort

Quicksort is a well-known sorting algorithm that, on average, makes O(n log n) comparisons to sort n items.

QUInt8 - Enum constant in enum class smile.deep.tensor.ScalarType

8-bit quantized unsigned tensor type which represents a compressed floating point tensor.

R

r - Variable in class smile.stat.distribution.NegativeBinomialDistribution

The number of failures until the experiment is stopped.

R() - Method in class smile.math.matrix.BigMatrix.QR

Returns the upper triangular factor.

R() - Method in class smile.math.matrix.fp32.Matrix.QR

Returns the upper triangular factor.

R() - Method in class smile.math.matrix.Matrix.QR

Returns the upper triangular factor.

r2 - Variable in class smile.validation.RegressionMetrics

The R-squared score on validation data.

R2 - Class in smile.validation.metric

R².

R2() - Constructor for class smile.validation.metric.R2

R2() - Method in class smile.timeseries.AR

Returns R² statistic.

R2() - Method in class smile.timeseries.ARMA

Returns R² statistic.

RadialBasisFunction - Interface in smile.math.rbf

A radial basis function (RBF) is a real-valued function whose value depends only on the distance from the origin, so that φ(x)=φ(||x||); or alternatively on the distance from some other point c, called a center, so that φ(x,c)=φ(||x-c||).

radius - Variable in class smile.clustering.DBSCAN

The neighborhood radius.

radius - Variable in class smile.clustering.MEC

The range of neighborhood.

radius(double) - Method in class smile.plot.vega.Mark

Sets the primary (outer) radius in pixels for arc mark, or polar coordinate radial offset of the text from the origin determined by the x and y properties for text marks.

radius2(double) - Method in class smile.plot.vega.Mark

Sets the secondary (inner) radius in pixels for arc mark.

radius2Offset(double) - Method in class smile.plot.vega.Mark

Sets the offset for radius2.

radiusOffset(double) - Method in class smile.plot.vega.Mark

Sets the offset for radius.

RADIX - Static variable in class smile.math.MathEx

The base of the exponent of the double type.

rainbow(int) - Static method in interface smile.plot.swing.Palette

Generate rainbow color palette.

rainbow(int, float) - Static method in interface smile.plot.swing.Palette

Generate rainbow color palette.

rainbow(int, float, float, float) - Static method in interface smile.plot.swing.Palette

Generate rainbow color palette.

rainbow(int, float, float, float, float, float) - Static method in interface smile.plot.swing.Palette

Generate rainbow color palette.

rand() - Method in class smile.stat.distribution.BernoulliDistribution

rand() - Method in class smile.stat.distribution.BetaDistribution

rand() - Method in class smile.stat.distribution.BinomialDistribution

This function generates a random variate with the binomial distribution.

rand() - Method in class smile.stat.distribution.ChiSquareDistribution

rand() - Method in class smile.stat.distribution.DiscreteMixture

rand() - Method in interface smile.stat.distribution.Distribution

Generates a random number following this distribution.

rand() - Method in class smile.stat.distribution.EmpiricalDistribution

rand() - Method in class smile.stat.distribution.ExponentialDistribution

rand() - Method in class smile.stat.distribution.FDistribution

rand() - Method in class smile.stat.distribution.GammaDistribution

Only support shape parameter k of integer.

rand() - Method in class smile.stat.distribution.GaussianDistribution

Generates a Gaussian random number with the Box-Muller algorithm.

rand() - Method in class smile.stat.distribution.GeometricDistribution

rand() - Method in class smile.stat.distribution.HyperGeometricDistribution

Uses inversion by chop-down search from the mode when the mean < 20 and the patchwork-rejection method when the mean >= 20.

rand() - Method in class smile.stat.distribution.KernelDensity

Random number generator.

rand() - Method in class smile.stat.distribution.LogisticDistribution

rand() - Method in class smile.stat.distribution.LogNormalDistribution

rand() - Method in class smile.stat.distribution.Mixture

rand() - Method in class smile.stat.distribution.MultivariateGaussianDistribution

Generate a random multivariate Gaussian sample.

rand() - Method in class smile.stat.distribution.NegativeBinomialDistribution

rand() - Method in class smile.stat.distribution.PoissonDistribution

This function generates a random variate with the poisson distribution.

rand() - Method in class smile.stat.distribution.ShiftedGeometricDistribution

rand() - Method in class smile.stat.distribution.TDistribution

rand() - Method in class smile.stat.distribution.WeibullDistribution

rand(int) - Method in interface smile.stat.distribution.Distribution

Generates a set of random numbers following this distribution.

rand(int) - Method in class smile.stat.distribution.MultivariateGaussianDistribution

Generates a set of random numbers following this distribution.

rand(int, int) - Static method in class smile.math.matrix.BigMatrix

Returns a uniformly distributed random matrix in [0, 1).

rand(int, int) - Static method in class smile.math.matrix.fp32.Matrix

Returns a uniformly distributed random matrix in [0, 1).

rand(int, int) - Static method in class smile.math.matrix.Matrix

Returns a uniformly distributed random matrix in [0, 1).

rand(int, int, double, double) - Static method in class smile.math.matrix.BigMatrix

Returns a random matrix of uniform distribution.

rand(int, int, double, double) - Static method in class smile.math.matrix.Matrix

Returns a uniformly distributed random matrix in given range.

rand(int, int, float, float) - Static method in class smile.math.matrix.fp32.Matrix

Returns a uniformly distributed random matrix in given range.

rand(int, int, Distribution) - Static method in class smile.math.matrix.BigMatrix

Returns a random matrix.

rand(int, int, Distribution) - Static method in class smile.math.matrix.fp32.Matrix

Returns a random matrix.

rand(int, int, Distribution) - Static method in class smile.math.matrix.Matrix

Returns a random matrix.

rand(long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor filled with values drawn from a uniform distribution on [0, 1).

rand(Tensor.Options, long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor filled with values drawn from a uniform distribution on [0, 1).

randi() - Method in class smile.stat.distribution.DiscreteDistribution

Generates an integer random number following this discrete distribution.

randi(int) - Method in class smile.stat.distribution.DiscreteDistribution

Generates a set of integer random numbers following this discrete distribution.

randi(int) - Method in class smile.stat.distribution.EmpiricalDistribution

RandIndex - Class in smile.validation.metric

Rand Index.

RandIndex() - Constructor for class smile.validation.metric.RandIndex

randn(int, int) - Static method in class smile.math.matrix.BigMatrix

Returns a random matrix of standard normal distribution.

randn(int, int) - Static method in class smile.math.matrix.fp32.Matrix

Returns a random matrix of standard normal distribution.

randn(int, int) - Static method in class smile.math.matrix.Matrix

Returns a random matrix of standard normal distribution.

randn(long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor filled with values drawn from a unit normal distribution.

randn(Tensor.Options, long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor filled with values drawn from a unit normal distribution.

random() - Method in class smile.hpo.Hyperparameters

Generates a stream of hyperparameters for random search.

random() - Static method in class smile.math.MathEx

Generate a random number in [0, 1).

random(double[]) - Static method in class smile.math.MathEx

Given a set of n probabilities, generate a random number in [0, n).

random(double[], int) - Static method in class smile.math.MathEx

Given a set of m probabilities, draw with replacement a set of n random number in [0, m).

random(double, double) - Static method in class smile.math.MathEx

Generate a uniform random number in the range [lo, hi).

random(double, double, int) - Static method in class smile.math.MathEx

Generate uniform random numbers in the range [lo, hi).

random(int) - Static method in class smile.math.MathEx

Generate n random numbers in [0, 1).

random(int, double) - Static method in interface smile.stat.Sampling

Simple random sampling.

Random - Class in smile.math

This is a high quality random number generator as a replacement of the standard Random class of Java system.

Random() - Constructor for class smile.math.Random

Initialize with default random number generator engine.

Random(long) - Constructor for class smile.math.Random

Initialize with given seed for default random number generator engine.

RandomForest - Class in smile.classification

Random forest for classification.

RandomForest - Class in smile.regression

Random forest for regression.

RandomForest(Formula, int, RandomForest.Model[], ClassificationMetrics, double[]) - Constructor for class smile.classification.RandomForest

Constructor.

RandomForest(Formula, int, RandomForest.Model[], ClassificationMetrics, double[], IntSet) - Constructor for class smile.classification.RandomForest

Constructor.

RandomForest(Formula, RandomForest.Model[], RegressionMetrics, double[]) - Constructor for class smile.regression.RandomForest

Constructor.

RandomForest.Model - Class in smile.classification

The base model.

RandomForest.Model - Class in smile.regression

The base model.

randomInt(int) - Static method in class smile.math.MathEx

Returns a random integer in [0, n).

randomInt(int, int) - Static method in class smile.math.MathEx

Returns a random integer in [lo, hi).

randomLong() - Static method in class smile.math.MathEx

Returns a random long integer.

RandomNumberGenerator - Interface in smile.math.random

Random number generator interface.

RandomProjection - Class in smile.feature.extraction

Random projection is a promising dimensionality reduction technique for learning mixtures of Gaussians.

RandomProjection(Matrix, String...) - Constructor for class smile.feature.extraction.RandomProjection

Constructor.

range() - Method in class smile.math.matrix.BigMatrix.SVD

Returns the matrix which columns are the orthonormal basis for the range space.

range() - Method in class smile.math.matrix.fp32.Matrix.SVD

Returns the matrix which columns are the orthonormal basis for the range space.

range() - Method in class smile.math.matrix.Matrix.SVD

Returns the matrix which columns are the orthonormal basis for the range space.

range(double...) - Method in class smile.plot.vega.Field

Sets the customize range values.

range(String...) - Method in class smile.plot.vega.Field

Sets the customize range values.

range(String, double, double) - Static method in class smile.plot.vega.Predicate

Test if a field in the data point satisfies certain conditions.

rangeMax(double) - Method in class smile.plot.vega.Field

Sets the maximum value in the scale range, overriding the range property or the default range.

rangeMax(String) - Method in class smile.plot.vega.Field

Sets the maximum value in the scale range, overriding the range property or the default range.

rangeMin(double) - Method in class smile.plot.vega.Field

Sets the minimum value in the scale range, overriding the range property or the default range.

rangeMin(String) - Method in class smile.plot.vega.Field

Sets the minimum value in the scale range, overriding the range property or the default range.

rank() - Method in class smile.math.matrix.BigMatrix.SVD

Returns the effective numerical matrix rank.

rank() - Method in class smile.math.matrix.fp32.Matrix.SVD

Returns the effective numerical matrix rank.

rank() - Method in class smile.math.matrix.Matrix.SVD

Returns the effective numerical matrix rank.

rank(int, int, long, long) - Method in class smile.nlp.relevance.TFIDF

Returns the relevance score between a term and a document based on a corpus.

rank(Corpus, TextTerms, String[], int[], int) - Method in class smile.nlp.relevance.BM25

rank(Corpus, TextTerms, String[], int[], int) - Method in interface smile.nlp.relevance.RelevanceRanker

Returns the relevance score between a set of terms and a document based on a corpus.

rank(Corpus, TextTerms, String[], int[], int) - Method in class smile.nlp.relevance.TFIDF

rank(Corpus, TextTerms, String, int, int) - Method in class smile.nlp.relevance.BM25

rank(Corpus, TextTerms, String, int, int) - Method in interface smile.nlp.relevance.RelevanceRanker

Returns the relevance score between a term and a document based on a corpus.

rank(Corpus, TextTerms, String, int, int) - Method in class smile.nlp.relevance.TFIDF

Rank() - Static method in interface smile.gap.Selection

Rank Selection.

RatioScale - Class in smile.data.measure

The ratio scale allows for both difference and ratio of two values.

RatioScale(NumberFormat) - Constructor for class smile.data.measure.RatioScale

Constructor.

rawinterp(int, double) - Method in class smile.interpolation.AbstractInterpolation

Subclasses provide this as the actual interpolation method.

rawinterp(int, double) - Method in class smile.interpolation.CubicSplineInterpolation1D

rawinterp(int, double) - Method in class smile.interpolation.LinearInterpolation

RB - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Adverb.

RBF<T> - Class in smile.base.rbf

A neuron in radial basis function network.

RBF(T, RadialBasisFunction, Metric<T>) - Constructor for class smile.base.rbf.RBF

Constructor.

RBFInterpolation - Class in smile.interpolation

Radial basis function interpolation is a popular method for the data points are irregularly distributed in space.

RBFInterpolation(double[][], double[], RadialBasisFunction) - Constructor for class smile.interpolation.RBFInterpolation

Constructor.

RBFInterpolation(double[][], double[], RadialBasisFunction, boolean) - Constructor for class smile.interpolation.RBFInterpolation

Constructor.

RBFInterpolation1D - Class in smile.interpolation

Radial basis function interpolation is a popular method for the data points are irregularly distributed in space.

RBFInterpolation1D(double[], double[], RadialBasisFunction) - Constructor for class smile.interpolation.RBFInterpolation1D

Constructor.

RBFInterpolation1D(double[], double[], RadialBasisFunction, boolean) - Constructor for class smile.interpolation.RBFInterpolation1D

Constructor.

RBFInterpolation2D - Class in smile.interpolation

Radial basis function interpolation is a popular method for the data points are irregularly distributed in space.

RBFInterpolation2D(double[], double[], double[], RadialBasisFunction) - Constructor for class smile.interpolation.RBFInterpolation2D

Constructor.

RBFInterpolation2D(double[], double[], double[], RadialBasisFunction, boolean) - Constructor for class smile.interpolation.RBFInterpolation2D

Constructor.

RBFNetwork<T> - Class in smile.classification

Radial basis function networks.

RBFNetwork<T> - Class in smile.regression

Radial basis function network.

RBFNetwork(int, RBF<T>[], Matrix, boolean) - Constructor for class smile.classification.RBFNetwork

Constructor.

RBFNetwork(int, RBF<T>[], Matrix, boolean, IntSet) - Constructor for class smile.classification.RBFNetwork

Constructor.

RBFNetwork(RBF<T>[], double[], boolean) - Constructor for class smile.regression.RBFNetwork

Constructor.

rbind(double[]...) - Static method in class smile.math.MathEx

Concatenates vectors by rows.

rbind(float[]...) - Static method in class smile.math.MathEx

Concatenates vectors by rows.

rbind(int[]...) - Static method in class smile.math.MathEx

Concatenates vectors by rows.

rbind(String[]...) - Static method in class smile.math.MathEx

Concatenates vectors by rows.

RBR - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Adverb, comparative.

RBS - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Adverb, superlative.

RDA - Class in smile.classification

Regularized discriminant analysis.

RDA(double[], double[][], double[][], Matrix[]) - Constructor for class smile.classification.RDA

Constructor.

RDA(double[], double[][], double[][], Matrix[], IntSet) - Constructor for class smile.classification.RDA

Constructor.

re - Variable in class smile.math.Complex

The real part.

read() - Method in class smile.io.Arff

Reads all the records.

read(int) - Method in class smile.io.Arff

Reads a limited number of records.

read(BufferedReader, int) - Method in class smile.io.JSON

Reads a limited number of records from a JSON file.

read(InputStream, int) - Method in class smile.io.Arrow

Reads a limited number of records from an arrow file.

read(InputStream, int) - Method in class smile.io.Avro

Reads a limited number of records from an avro file.

read(InputStream, int) - Static method in interface smile.io.SAS

Reads a limited number of records from a SAS7BDAT file.

read(String) - Method in class smile.io.Arrow

Reads a limited number of records from an arrow file.

read(String) - Method in class smile.io.Avro

Reads an avro file.

read(String) - Method in class smile.io.CSV

Reads a CSV file.

read(String) - Method in class smile.io.JSON

Reads a JSON file.

read(String) - Static method in class smile.io.Parquet

Reads a HDFS parquet file.

read(String) - Static method in interface smile.io.SAS

Reads a SAS7BDAT file.

read(String, int) - Method in class smile.io.Arrow

Reads a limited number of records from an arrow file.

read(String, int) - Method in class smile.io.CSV

Reads a limited number of records from a CSV file.

read(String, int) - Method in class smile.io.JSON

Reads a JSON file.

read(String, int) - Static method in class smile.io.Parquet

Reads a HDFS parquet file.

read(Path) - Method in class smile.io.Arrow

Reads an arrow file.

read(Path) - Method in class smile.io.Avro

Reads an avro file.

read(Path) - Method in class smile.io.CSV

Reads a CSV file.

read(Path) - Method in class smile.io.JSON

Reads a JSON file.

read(Path) - Static method in class smile.io.Parquet

Reads a local parquet file.

read(Path) - Static method in interface smile.io.SAS

Reads a SAS7BDAT file.

read(Path, int) - Method in class smile.io.Arrow

Reads an arrow file.

read(Path, int) - Method in class smile.io.CSV

Reads a limited number of records from a CSV file.

read(Path, int) - Method in class smile.io.JSON

Reads a JSON file.

read(Path, int) - Static method in class smile.io.Parquet

Reads a local parquet file.

read(Path, List<String[]>, List<PennTreebankPOS[]>) - Static method in class smile.nlp.pos.HMMPOSTagger

Load training data from a corpora.

read(InputFile) - Static method in class smile.io.Parquet

Reads a parquet file.

read(InputFile, int) - Static method in class smile.io.Parquet

Reads a limited number of records from a parquet file.

Read - Interface in smile.io

Reads data from external storage systems.

reader(String) - Static method in interface smile.io.HadoopInput

Returns the reader of a file path or URI.

reader(String) - Static method in interface smile.io.Input

Returns the reader of a file path or URI.

reader(String, Charset) - Static method in interface smile.io.HadoopInput

Returns the reader of a file path or URI.

reader(String, Charset) - Static method in interface smile.io.Input

Returns the reader of a file path or URI.

Recall - Class in smile.deep.metric

Recall or true positive rate (TPR) (also called hit rate, sensitivity) is a statistical measures of the performance of a binary classification test.

Recall - Class in smile.validation.metric

In information retrieval area, sensitivity is called recall.

Recall() - Constructor for class smile.deep.metric.Recall

Constructor.

Recall() - Constructor for class smile.validation.metric.Recall

Recall(double) - Constructor for class smile.deep.metric.Recall

Constructor.

Recall(Averaging) - Constructor for class smile.deep.metric.Recall

Constructor.

reciprocal() - Method in class smile.math.Complex

Returns the reciprocal.

rectifier() - Static method in interface smile.base.mlp.ActivationFunction

The rectifier activation function max(0, x).

rectifier(int) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with rectified linear activation function.

rectifier(int, double) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with rectified linear activation function.

RED - Static variable in interface smile.plot.swing.Palette

redblue(int) - Static method in interface smile.plot.swing.Palette

Generate red-blue color palette.

redblue(int, float) - Static method in interface smile.plot.swing.Palette

Generate red-blue color palette.

redgreen(int) - Static method in interface smile.plot.swing.Palette

Generate red-green color palette.

redgreen(int, float) - Static method in interface smile.plot.swing.Palette

Generate red-green color palette.

References - Search tag in class smile.anomaly.IsolationForest

Section

References - Search tag in class smile.anomaly.SVM

Section

References - Search tag in class smile.association.FPGrowth

Section

References - Search tag in class smile.base.svm.SVR

Section

References - Search tag in class smile.classification.AdaBoost

Section

References - Search tag in class smile.classification.DiscreteNaiveBayes

Section

References - Search tag in class smile.classification.FLD

Section

References - Search tag in class smile.classification.GradientTreeBoost

Section

References - Search tag in class smile.classification.IsotonicRegressionScaling

Section

References - Search tag in class smile.classification.Maxent

Section

References - Search tag in class smile.classification.NaiveBayes

Section

References - Search tag in class smile.classification.PlattScaling

Section

References - Search tag in class smile.classification.RBFNetwork

Section

References - Search tag in class smile.classification.SVM

Section

References - Search tag in class smile.clustering.BBDTree

Section

References - Search tag in class smile.clustering.CLARANS

Section

References - Search tag in class smile.clustering.DBSCAN

Section

References - Search tag in class smile.clustering.DENCLUE

Section

References - Search tag in class smile.clustering.DeterministicAnnealing

Section

References - Search tag in class smile.clustering.GMeans

Section

References - Search tag in class smile.clustering.HierarchicalClustering

Section

References - Search tag in class smile.clustering.KMeans

Section

References - Search tag in class smile.clustering.KModes

Section

References - Search tag in class smile.clustering.MEC

Section

References - Search tag in class smile.clustering.SIB

Section

References - Search tag in class smile.clustering.SpectralClustering

Section

References - Search tag in class smile.clustering.XMeans

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Section

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Section

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Section

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Section

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Section

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Section

Regex - Interface in smile.util

Regular expression patterns.

regression(int, int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.CrossValidation

Repeated cross validation of regression.

regression(int, int, T[], double[], BiFunction<T[], double[], M>) - Static method in interface smile.validation.CrossValidation

Repeated cross validation of regression.

regression(int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.Bootstrap

Runs regression bootstrap validation.

regression(int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.CrossValidation

Cross validation of regression.

regression(int, T[], double[], BiFunction<T[], double[], M>) - Static method in interface smile.validation.Bootstrap

Runs regression bootstrap validation.

regression(int, T[], double[], BiFunction<T[], double[], M>) - Static method in interface smile.validation.CrossValidation

Cross validation of regression.

regression(String, String) - Method in class smile.plot.vega.Transform

Adds a regression transform.

regression(Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameRegression>) - Static method in interface smile.validation.LOOCV

Runs leave-one-out cross validation tests.

regression(T[], double[], BiFunction<T[], double[], M>) - Static method in interface smile.validation.LOOCV

Runs leave-one-out cross validation tests.

Regression<T> - Interface in smile.regression

Regression analysis includes any techniques for modeling and analyzing the relationship between a dependent variable and one or more independent variables.

Regression.Trainer<T,M> - Interface in smile.regression

The regression trainer.

RegressionMetric - Interface in smile.validation.metric

An abstract interface to measure the regression performance.

RegressionMetrics - Class in smile.validation

The regression validation metrics.

RegressionMetrics(double, double, int, double, double, double, double, double) - Constructor for class smile.validation.RegressionMetrics

Constructor.

RegressionNode - Class in smile.base.cart

A leaf node in regression tree.

RegressionNode(int, double, double, double) - Constructor for class smile.base.cart.RegressionNode

Constructor.

RegressionTransform - Class in smile.plot.vega

The regression transform fits two-dimensional regression models to smooth and predict data.

RegressionTree - Class in smile.regression

Regression tree.

RegressionTree(DataFrame, Loss, StructField, int, int, int, int, int[], int[][]) - Constructor for class smile.regression.RegressionTree

Constructor.

RegressionValidation<M> - Class in smile.validation

Regression model validation results.

RegressionValidation(M, double[], double[], RegressionMetrics) - Constructor for class smile.validation.RegressionValidation

Constructor.

RegressionValidations<M> - Class in smile.validation

Regression model validation results.

RegressionValidations(List<RegressionValidation<M>>) - Constructor for class smile.validation.RegressionValidations

Constructor.

regressors - Variable in class smile.regression.GaussianProcessRegression

The regressors.

regularizedIncompleteBetaFunction(double, double, double) - Static method in class smile.math.special.Beta

Regularized Incomplete Beta function.

regularizedIncompleteGamma(double, double) - Static method in class smile.math.special.Gamma

Regularized Incomplete Gamma Function P(s,x) = ∫₀^x e^-t t^(s-1) dt

regularizedUpperIncompleteGamma(double, double) - Static method in class smile.math.special.Gamma

Regularized Upper/Complementary Incomplete Gamma Function Q(s,x) = 1 - P(s,x) = 1 - ∫₀^x e^-t t^(s-1) dt

rejectionSampling(double, double, double) - Method in interface smile.stat.distribution.Distribution

Use the rejection technique to draw a sample from the given distribution.

Relevance - Class in smile.nlp.relevance

In the context of information retrieval, relevance denotes how well a retrieved set of documents meets the information need of the user.

Relevance(Text, double) - Constructor for class smile.nlp.relevance.Relevance

Constructor.

RelevanceRanker - Interface in smile.nlp.relevance

An interface to provide relevance ranking algorithm.

relu() - Static method in interface smile.base.mlp.activation.ActivationFunction

Returns the rectifier activation function max(0, x).

relu(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with ReLU activation function.

relu(int, int, double) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with ReLU activation function.

ReLU - Class in smile.base.mlp.activation

The rectifier activation function max(0, x).

ReLU - Class in smile.deep.activation

Rectified Linear Unit activation function.

ReLU() - Constructor for class smile.base.mlp.activation.ReLU

Constructor.

ReLU(boolean) - Constructor for class smile.deep.activation.ReLU

Constructor.

remove(double[], E) - Method in class smile.neighbor.MutableLSH

Remove an entry from the hash table.

remove(int) - Method in class smile.neighbor.lsh.Bucket

Removes a point from bucket.

remove(int) - Method in class smile.util.DoubleArrayList

Removes the value at specified index from the list.

remove(int) - Method in class smile.util.IntArrayList

Removes the value at specified index from the list.

remove(int) - Method in class smile.util.IntDoubleHashMap

Removes the mapping for the specified key from this map if present.

remove(int) - Method in class smile.util.IntHashSet

Removes the specified element from this set if it is present.

remove(int) - Method in class smile.util.SparseArray

Removes an entry.

remove(Plot) - Method in class smile.plot.swing.Canvas

Remove a graphical shape from the canvas.

remove(PlotPanel) - Method in class smile.plot.swing.PlotGrid

Remove a plot from the frame.

remove(Shape) - Method in class smile.plot.swing.Canvas

Remove a graphical shape from the canvas.

removeChild(Concept) - Method in class smile.taxonomy.Concept

Removes a child to this node.

removeEdge(int, int) - Method in class smile.graph.AdjacencyList

removeEdge(int, int) - Method in class smile.graph.AdjacencyMatrix

removeEdge(int, int) - Method in interface smile.graph.Graph

In a simple graph, removes and returns the edge going from the specified source vertex to the specified target vertex.

removeEdge(Graph.Edge) - Method in class smile.graph.AdjacencyList

removeEdge(Graph.Edge) - Method in class smile.graph.AdjacencyMatrix

removeEdge(Graph.Edge) - Method in interface smile.graph.Graph

Removes the specified edge from the graph.

removeEdge(Neuron) - Method in class smile.vq.hebb.Neuron

Removes an edge.

removeEdges(Collection<Graph.Edge>) - Method in class smile.graph.AdjacencyList

removeEdges(Collection<Graph.Edge>) - Method in class smile.graph.AdjacencyMatrix

removeEdges(Collection<Graph.Edge>) - Method in interface smile.graph.Graph

Removes a set of edges from the graph.

removeKeyword(String) - Method in class smile.taxonomy.Concept

Removes a keyword from the concept synset.

removeLegend() - Method in class smile.plot.vega.Field

Removes the legend for the encoding channel will be removed.

removePropertyChangeListener(PropertyChangeListener) - Method in class smile.plot.swing.Canvas

Remove a PropertyChangeListener from the listener list.

Repeat - Class in smile.plot.vega

Repeat a View.

Repeat(VegaLite, String...) - Constructor for class smile.plot.vega.Repeat

Creates a view for each entry in an array of fields.

Repeat(VegaLite, String[], String[]) - Constructor for class smile.plot.vega.Repeat

Creates a view for each entry in an array of fields.

replace(Node, Node) - Method in class smile.base.cart.InternalNode

Returns a new internal node with children replaced.

replace(Node, Node) - Method in class smile.base.cart.NominalNode

replace(Node, Node) - Method in class smile.base.cart.OrdinalNode

replaceNaN(double) - Method in class smile.math.matrix.BigMatrix

Replaces NaN's with given value.

replaceNaN(double) - Method in class smile.math.matrix.Matrix

Replaces NaN's with given value.

replaceNaN(double) - Method in class smile.util.Array2D

Replaces NaN values with x.

replaceNaN(float) - Method in class smile.math.matrix.fp32.Matrix

Replaces NaN's with given value.

requireGrad() - Method in class smile.deep.tensor.Tensor

Returns true if autograd should record operations on this tensor.

requireGrad(boolean) - Method in class smile.deep.tensor.Tensor

Sets if autograd should record operations on this tensor.

requireGradients(boolean) - Method in class smile.deep.tensor.Tensor.Options

Set true if gradients need to be computed for this tensor.

reset() - Method in class smile.deep.metric.Accuracy

reset() - Method in interface smile.deep.metric.Metric

Resets the metric state variables to their default value.

reset() - Method in class smile.deep.metric.Precision

reset() - Method in class smile.deep.metric.Recall

reset() - Method in class smile.deep.Optimizer

Resets gradients.

reset() - Method in class smile.plot.swing.Axis

Set the base coordinate space.

reset() - Method in class smile.plot.swing.Base

Reset base coordinates.

reset() - Method in class smile.plot.swing.PlotPanel

Resets the plot.

resetProjection() - Method in class smile.plot.swing.Graphics

Reset projection object when the PlotCanvas size changed.

reshape(long...) - Method in class smile.deep.tensor.Tensor

Returns a tensor with the same data and number of elements but with the specified shape.

residual() - Method in interface smile.base.cart.Loss

Returns the residual vector.

residuals - Variable in class smile.math.LevenbergMarquardt

The residuals.

residuals() - Method in class smile.regression.LinearModel

Returns the residuals, which is response minus fitted values.

residuals() - Method in class smile.timeseries.AR

Returns the residuals, that is response minus fitted values.

residuals() - Method in class smile.timeseries.ARMA

Returns the residuals, that is response minus fitted values.

resize(BufferedImage, int, int) - Method in interface smile.vision.transform.Transform

Resizes an image and keeps the aspect ratio.

resolveAxis(String, String) - Method in class smile.plot.vega.Concat

resolveAxis(String, String) - Method in class smile.plot.vega.Facet

resolveAxis(String, String) - Method in class smile.plot.vega.Layer

resolveAxis(String, String) - Method in class smile.plot.vega.Repeat

resolveAxis(String, String) - Method in interface smile.plot.vega.ViewComposition

Sets an axis resolution.

resolveLegend(String, String) - Method in class smile.plot.vega.Concat

resolveLegend(String, String) - Method in class smile.plot.vega.Facet

resolveLegend(String, String) - Method in class smile.plot.vega.Layer

resolveLegend(String, String) - Method in class smile.plot.vega.Repeat

resolveLegend(String, String) - Method in interface smile.plot.vega.ViewComposition

Sets a legend resolution.

resolveScale(String, String) - Method in class smile.plot.vega.Concat

resolveScale(String, String) - Method in class smile.plot.vega.Facet

resolveScale(String, String) - Method in class smile.plot.vega.Layer

resolveScale(String, String) - Method in class smile.plot.vega.Repeat

resolveScale(String, String) - Method in interface smile.plot.vega.ViewComposition

Sets a scale resolution.

response - Variable in class smile.base.cart.CART

The schema of response variable.

response() - Method in interface smile.base.cart.Loss

Returns the response variable for next iteration.

response() - Method in class smile.data.formula.Formula

Returns the response term.

reverse(double[]) - Static method in class smile.math.MathEx

Reverses the order of the elements in the specified array.

reverse(float[]) - Static method in class smile.math.MathEx

Reverses the order of the elements in the specified array.

reverse(int[]) - Static method in class smile.math.MathEx

Reverses the order of the elements in the specified array.

reverse(T[]) - Static method in class smile.math.MathEx

Reverses the order of the elements in the specified array.

rho - Variable in class smile.base.mlp.MultilayerPerceptron

The discounting factor for the history/coming gradient in RMSProp.

rhs(String...) - Static method in class smile.data.formula.Formula

Factory method.

rhs(Term...) - Static method in class smile.data.formula.Formula

Factory method.

RidgeRegression - Class in smile.regression

Ridge Regression.

RidgeRegression() - Constructor for class smile.regression.RidgeRegression

RIGHT - Enum constant in enum class smile.math.blas.Side

B * A

rightPad(String, int, char) - Static method in interface smile.util.Strings

Right pad a string with a specified character.

rint(String) - Static method in interface smile.data.formula.Terms

The rint(x) term.

rint(Term) - Static method in interface smile.data.formula.Terms

The rint(x) term.

rmse - Variable in class smile.validation.RegressionMetrics

The root mean squared error on validation data.

RMSE - Class in smile.validation.metric

Root mean squared error.

RMSE() - Constructor for class smile.validation.metric.RMSE

RMSprop(Model, double) - Static method in class smile.deep.Optimizer

Returns an RMSprop optimizer.

RMSprop(Model, double, double, double, double, double, boolean) - Static method in class smile.deep.Optimizer

Returns an RMSprop optimizer.

RMSProp - Class in smile.base.mlp.optimizer

RMSProp optimizer with adaptive learning rate.

RMSProp() - Constructor for class smile.base.mlp.optimizer.RMSProp

Constructor.

RMSProp(TimeFunction) - Constructor for class smile.base.mlp.optimizer.RMSProp

Constructor.

RMSProp(TimeFunction, double, double) - Constructor for class smile.base.mlp.optimizer.RMSProp

Constructor.

RNNSearch<K,V> - Interface in smile.neighbor

Retrieves the nearest neighbors to a query in a radius.

RobustStandardizer - Class in smile.feature.transform

Robustly standardizes numeric feature by subtracting the median and dividing by the IQR.

RobustStandardizer() - Constructor for class smile.feature.transform.RobustStandardizer

root - Variable in class smile.base.cart.CART

The root of decision tree.

root() - Method in class smile.base.cart.CART

Returs the root node.

Root - Class in smile.math

Root finding algorithms.

rotate(double, double) - Method in class smile.plot.swing.Graphics

Rotate the 3D view based on the changes on mouse position.

rotate(double, double, double) - Method in class smile.plot.vega.Projection

Sets the projection's three-axis rotation to the specified angles by specifying the rotation angles in degrees about each spherical axis.

RouletteWheel() - Static method in interface smile.gap.Selection

Roulette Wheel Selection, also called fitness proportionate selection.

round(double, int) - Static method in class smile.math.MathEx

Round a double vale to given digits such as 10^n, where n is a positive or negative integer.

round(String) - Static method in interface smile.data.formula.Terms

The round(x) term.

round(Term) - Static method in interface smile.data.formula.Terms

The round(x) term.

ROUND_STYLE - Static variable in class smile.math.MathEx

Rounding style.

rounds - Variable in class smile.validation.ClassificationValidations

The multiple round validations.

rounds - Variable in class smile.validation.RegressionValidations

The multiple round validations.

row(double[]) - Static method in class smile.math.matrix.BigMatrix

Returns a row vector/matrix.

row(double[]) - Static method in class smile.math.matrix.fp32.Matrix

Returns a row vector/matrix.

row(double[]) - Static method in class smile.math.matrix.Matrix

Returns a row vector/matrix.

row(double[], int, int) - Static method in class smile.math.matrix.BigMatrix

Returns a row vector/matrix.

row(double[], int, int) - Static method in class smile.math.matrix.fp32.Matrix

Returns a row vector/matrix.

row(double[], int, int) - Static method in class smile.math.matrix.Matrix

Returns a row vector/matrix.

row(float[]) - Static method in class smile.math.matrix.fp32.Matrix

Returns a row vector/matrix.

row(float[], int, int) - Static method in class smile.math.matrix.fp32.Matrix

Returns a row vector/matrix.

row(int) - Method in class smile.math.matrix.BigMatrix

Returns the i-th row.

row(int) - Method in class smile.math.matrix.fp32.Matrix

Returns the i-th row.

row(int) - Method in class smile.math.matrix.Matrix

Returns the i-th row.

row(int...) - Method in class smile.math.matrix.BigMatrix

Returns the matrix of selected rows.

row(String) - Method in class smile.plot.vega.Facet

Returns the field definition for the horizontal facet of trellis plots.

ROW_MAJOR - Enum constant in enum class smile.math.blas.Layout

Row major layout.

RowHeader() - Constructor for class smile.swing.Table.RowHeader

Constructor.

rowMax(double[][]) - Static method in class smile.math.MathEx

Returns the row maximum of a matrix.

rowMax(int[][]) - Static method in class smile.math.MathEx

Returns the row maximum of a matrix.

rowMeans() - Method in class smile.math.matrix.BigMatrix

Returns the mean of each row.

rowMeans() - Method in class smile.math.matrix.fp32.Matrix

Returns the mean of each row.

rowMeans() - Method in class smile.math.matrix.Matrix

Returns the mean of each row.

rowMeans(double[][]) - Static method in class smile.math.MathEx

Returns the row means of a matrix.

rowMin(double[][]) - Static method in class smile.math.MathEx

Returns the row minimum of a matrix.

rowMin(int[][]) - Static method in class smile.math.MathEx

Returns the row minimum of a matrix.

rowName(int) - Method in class smile.math.matrix.fp32.IMatrix

Returns the name of i-th row.

rowName(int) - Method in class smile.math.matrix.IMatrix

Returns the name of i-th row.

rowNames() - Method in class smile.math.matrix.fp32.IMatrix

Returns the row names.

rowNames() - Method in class smile.math.matrix.IMatrix

Returns the row names.

rowNames(String[]) - Method in class smile.math.matrix.fp32.IMatrix

Sets the row names.

rowNames(String[]) - Method in class smile.math.matrix.IMatrix

Sets the row names.

rowPadding(double) - Method in class smile.plot.vega.Legend

Sets the vertical padding in pixels between symbol legend entries.

rows(int...) - Method in class smile.math.matrix.fp32.Matrix

Returns the matrix of selected rows.

rows(int...) - Method in class smile.math.matrix.Matrix

Returns the matrix of selected rows.

rowSds() - Method in class smile.math.matrix.BigMatrix

Returns the standard deviations of each row.

rowSds() - Method in class smile.math.matrix.fp32.Matrix

Returns the standard deviations of each row.

rowSds() - Method in class smile.math.matrix.Matrix

Returns the standard deviations of each row.

rowSds(double[][]) - Static method in class smile.math.MathEx

Returns the row standard deviations of a matrix.

rowSums() - Method in class smile.math.matrix.BigMatrix

Returns the sum of each row.

rowSums() - Method in class smile.math.matrix.fp32.Matrix

Returns the sum of each row.

rowSums() - Method in class smile.math.matrix.Matrix

Returns the sum of each row.

rowSums(double[][]) - Static method in class smile.math.MathEx

Returns the row sums of a matrix.

rowSums(int[][]) - Static method in class smile.math.MathEx

Returns the row sums of a matrix.

ROYAL_BLUE - Static variable in interface smile.plot.swing.Palette

RP - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Particle.

RSquared() - Method in class smile.regression.LinearModel

Returns R² statistic.

rss - Variable in class smile.validation.RegressionMetrics

The residual sum of squares on validation data.

RSS - Class in smile.validation.metric

Residual sum of squares.

RSS() - Constructor for class smile.validation.metric.RSS

RSS() - Method in class smile.regression.LinearModel

Returns the residual sum of squares.

RSS() - Method in class smile.timeseries.AR

Returns the residual sum of squares.

RSS() - Method in class smile.timeseries.ARMA

Returns the residual sum of squares.

run(int, Supplier<T>) - Static method in class smile.clustering.PartitionClustering

Runs a clustering algorithm multiple times and return the best one (e.g.

rutherford(Path) - Static method in class smile.math.matrix.fp32.SparseMatrix

Reads a sparse matrix from a Rutherford-Boeing Exchange Format file.

rutherford(Path) - Static method in class smile.math.matrix.SparseMatrix

Reads a sparse matrix from a Rutherford-Boeing Exchange Format file.

S

s - Variable in class smile.math.matrix.BigMatrix.SVD

The singular values in descending order.

s - Variable in class smile.math.matrix.fp32.Matrix.SVD

The singular values in descending order.

s - Variable in class smile.math.matrix.Matrix.SVD

The singular values in descending order.

s2n - Variable in class smile.feature.selection.SignalNoiseRatio

Signal noise ratio.

SA - Enum constant in enum class smile.math.matrix.ARPACK.SymmOption

The smallest algebraic eigenvalues.

SA - Enum constant in enum class smile.math.matrix.fp32.ARPACK.SymmOption

The smallest algebraic eigenvalues.

SALMON - Static variable in interface smile.plot.swing.Palette

SammonMapping - Class in smile.manifold

The Sammon's mapping is an iterative technique for making interpoint distances in the low-dimensional projection as close as possible to the interpoint distances in the high-dimensional object.

SammonMapping(double, double[][]) - Constructor for class smile.manifold.SammonMapping

Constructor.

sample(int) - Method in class smile.plot.vega.Transform

Adds a sample transform.

sample(int) - Method in class smile.regression.GaussianProcessRegression.JointPrediction

Draw samples from Gaussian process.

SampleBatch - Record Class in smile.deep

A min-batch dataset consists of data and an associated target (label).

SampleBatch(Tensor, Tensor) - Constructor for record class smile.deep.SampleBatch

Creates an instance of a SampleBatch record class.

SampleInstance<D,T> - Record Class in smile.data

An immutable sample instance.

SampleInstance(D) - Constructor for record class smile.data.SampleInstance

Constructor without target.

SampleInstance(D, T) - Constructor for record class smile.data.SampleInstance

Creates an instance of a SampleInstance record class.

samples - Variable in class smile.base.cart.CART

The samples for training this node.

samples - Variable in class smile.validation.Bag

The random samples.

Sampling - Interface in smile.stat

Random sampling is the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population.

sas(String) - Static method in interface smile.io.Read

Reads a SAS7BDAT file.

sas(Path) - Static method in interface smile.io.Read

Reads a SAS7BDAT file.

SAS - Interface in smile.io

Reads SAS7BDAT datasets.

save() - Method in class smile.plot.swing.PlotGrid

Shows a file chooser and exports the plot to the selected image file.

save() - Method in class smile.plot.swing.PlotPanel

Shows a file chooser and exports the plot to the selected image file.

save(File) - Method in class smile.plot.swing.PlotGrid

Exports the plot to an image file.

save(File) - Method in class smile.plot.swing.PlotPanel

Exports the plot to an image file.

save(String) - Method in class smile.deep.Model

Serialize the model as a checkpoint.

sbmv(Layout, UPLO, int, int, double, double[], int, double[], int, double, double[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric band matrix.

sbmv(Layout, UPLO, int, int, double, double[], int, double[], int, double, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

sbmv(Layout, UPLO, int, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric band matrix.

sbmv(Layout, UPLO, int, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

sbmv(Layout, UPLO, int, int, float, float[], int, float[], int, float, float[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric band matrix.

sbmv(Layout, UPLO, int, int, float, float[], int, float[], int, float, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

sbmv(Layout, UPLO, int, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric band matrix.

sbmv(Layout, UPLO, int, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

scal(double, double[]) - Method in interface smile.math.blas.BLAS

Scales a vector with a scalar.

scal(float, float[]) - Method in interface smile.math.blas.BLAS

Scales a vector with a scalar.

scal(int, double, double[], int) - Method in interface smile.math.blas.BLAS

Scales a vector with a scalar.

scal(int, double, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

scal(int, float, float[], int) - Method in interface smile.math.blas.BLAS

Scales a vector with a scalar.

scal(int, float, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

ScalarType - Enum Class in smile.deep.tensor

The data type of the elements stored in the tensor.

scale - Variable in class smile.stat.distribution.LogisticDistribution

The scale parameter.

scale() - Method in class smile.classification.ClassLabels

Returns the nominal scale of the class labels.

scale() - Method in class smile.math.kernel.Gaussian

Returns the length scale of kernel.

scale() - Method in class smile.math.kernel.HyperbolicTangent

Returns the scale of kernel.

scale() - Method in class smile.math.kernel.Laplacian

Returns the length scale of kernel.

scale() - Method in class smile.math.kernel.Matern

Returns the length scale of kernel.

scale() - Method in class smile.math.kernel.Polynomial

Returns the scale of kernel.

scale() - Method in class smile.math.kernel.ThinPlateSpline

Returns the length scale of kernel.

scale(double) - Method in class smile.classification.PlattScaling

Returns the posterior probability estimate P(y = 1 | x).

scale(double) - Method in class smile.math.Complex

Scalar multiplication.

scale(double) - Method in class smile.plot.vega.Projection

Sets the projection's scale (zoom) factor, overriding automatic fitting.

scale(double[][]) - Static method in class smile.math.MathEx

Scales each column of a matrix to range [0, 1].

scale(double[], double[]) - Method in class smile.math.matrix.BigMatrix

Centers and scales the columns of matrix.

scale(double[], double[]) - Method in class smile.math.matrix.Matrix

Centers and scales the columns of matrix.

scale(double, double[]) - Static method in class smile.math.MathEx

Scale each element of an array by a constant x = a * x.

scale(double, double[], double[]) - Static method in class smile.math.MathEx

Scale each element of an array by a constant y = a * x.

scale(float[], float[]) - Method in class smile.math.matrix.fp32.Matrix

Centers and scales the columns of matrix.

scale(String) - Method in class smile.plot.vega.Field

Sets the function that transforms values in the data domain (numbers, dates, strings, etc.) to visual values (pixels, colors, sizes) for position and mark property channels.

ScaledRouletteWheel() - Static method in interface smile.gap.Selection

Scaled Roulette Wheel Selection.

Scaler - Class in smile.feature.transform

Scales the numeric variables into the range [0, 1].

Scaler - Class in smile.math

Affine transformation y = (x - offset) / scale.

Scaler() - Constructor for class smile.feature.transform.Scaler

Scaler(double, double, boolean) - Constructor for class smile.math.Scaler

Constructor.

scatter() - Method in class smile.stat.distribution.MultivariateGaussianDistribution

Returns the scatter of distribution, which is defined as |Σ|.

ScatterPlot - Class in smile.plot.swing

The data is displayed as a collection of points.

ScatterPlot(Point...) - Constructor for class smile.plot.swing.ScatterPlot

Constructor.

ScatterPlot(Point[], Legend[]) - Constructor for class smile.plot.swing.ScatterPlot

Constructor.

scatterReduce(int, Tensor, Tensor, String) - Method in class smile.deep.tensor.Tensor

Writes all values from the tensor src into this tensor at the indices specified in the index tensor.

scatterReduce_(int, Tensor, Tensor, String) - Method in class smile.deep.tensor.Tensor

Writes all values from the tensor src into this tensor at the indices specified in the index tensor.

schema - Variable in class smile.base.cart.CART

The schema of predictors.

schema - Variable in class smile.feature.extraction.Projection

The schema of output space.

schema() - Method in class smile.classification.AdaBoost

schema() - Method in interface smile.classification.DataFrameClassifier

Returns the predictor schema.

schema() - Method in class smile.classification.DecisionTree

schema() - Method in class smile.classification.GradientTreeBoost

schema() - Method in class smile.classification.RandomForest

schema() - Method in interface smile.data.DataFrame

Returns the schema of DataFrame.

schema() - Method in class smile.data.IndexDataFrame

schema() - Method in interface smile.data.Tuple

Returns the schema of tuple.

schema() - Method in class smile.io.Arff

Returns the data schema.

schema() - Method in interface smile.regression.DataFrameRegression

Returns the schema of predictors.

schema() - Method in class smile.regression.GradientTreeBoost

schema() - Method in class smile.regression.LinearModel

schema() - Method in class smile.regression.RandomForest

schema() - Method in class smile.regression.RegressionTree

schema(StructType) - Method in class smile.io.CSV

Sets the schema.

schema(StructType) - Method in class smile.io.JSON

Sets the schema.

score - Variable in class smile.nlp.collocation.Bigram

The chi-square statistical score of the collocation.

score - Variable in class smile.nlp.relevance.Relevance

The relevance score.

score() - Method in class smile.base.cart.InternalNode

Returns the split score (reduction of impurity).

score(double[]) - Method in class smile.anomaly.IsolationForest

Returns the anomaly score.

score(double[]) - Method in class smile.classification.LogisticRegression.Binomial

score(double[][]) - Method in class smile.anomaly.IsolationForest

Returns the anomaly scores.

score(double[], double[]) - Method in class smile.validation.metric.MAD

score(double[], double[]) - Method in class smile.validation.metric.MSE

score(double[], double[]) - Method in class smile.validation.metric.R2

score(double[], double[]) - Method in interface smile.validation.metric.RegressionMetric

Returns a score to measure the quality of regression.

score(double[], double[]) - Method in class smile.validation.metric.RMSE

score(double[], double[]) - Method in class smile.validation.metric.RSS

score(double, int, double, long, long) - Method in class smile.nlp.relevance.BM25

Returns the relevance score between a term and a document based on a corpus.

score(double, long, long) - Method in class smile.nlp.relevance.BM25

Returns the relevance score between a term and a document based on a corpus.

score(int[]) - Method in class smile.classification.Maxent.Binomial

score(int[], double[]) - Method in class smile.validation.metric.AUC

score(int[], double[]) - Method in class smile.validation.metric.LogLoss

score(int[], double[]) - Method in interface smile.validation.metric.ProbabilisticClassificationMetric

Returns a score to measure the quality of classification.

score(int[], int[]) - Method in class smile.validation.metric.Accuracy

score(int[], int[]) - Method in class smile.validation.metric.AdjustedMutualInformation

score(int[], int[]) - Method in class smile.validation.metric.AdjustedRandIndex

score(int[], int[]) - Method in interface smile.validation.metric.ClassificationMetric

Returns a score to measure the quality of classification.

score(int[], int[]) - Method in interface smile.validation.metric.ClusteringMetric

Returns a score to measure the quality of clustering.

score(int[], int[]) - Method in class smile.validation.metric.Error

score(int[], int[]) - Method in class smile.validation.metric.Fallout

score(int[], int[]) - Method in class smile.validation.metric.FDR

score(int[], int[]) - Method in class smile.validation.metric.FScore

score(int[], int[]) - Method in class smile.validation.metric.MatthewsCorrelation

score(int[], int[]) - Method in class smile.validation.metric.MutualInformation

score(int[], int[]) - Method in class smile.validation.metric.NormalizedMutualInformation

score(int[], int[]) - Method in class smile.validation.metric.Precision

score(int[], int[]) - Method in class smile.validation.metric.RandIndex

score(int[], int[]) - Method in class smile.validation.metric.Recall

score(int[], int[]) - Method in class smile.validation.metric.Sensitivity

score(int[], int[]) - Method in class smile.validation.metric.Specificity

score(int, int, double, int, int, double, int, int, double, long, long) - Method in class smile.nlp.relevance.BM25

Returns the relevance score between a term and a document based on a corpus.

score(SparseArray) - Method in class smile.classification.SparseLogisticRegression.Binomial

score(T) - Method in class smile.base.svm.KernelMachine

Returns the decision function value.

score(T) - Method in interface smile.classification.Classifier

The raw prediction score.

score(T) - Method in interface smile.gap.Fitness

Returns the non-negative fitness value of a chromosome.

scores - Variable in class smile.manifold.MDS

The component scores.

scoreTime - Variable in class smile.validation.ClassificationMetrics

The time in milliseconds of scoring the validation data.

scoreTime - Variable in class smile.validation.RegressionMetrics

The time in milliseconds of scoring the validation data.

scott(double[]) - Static method in interface smile.math.Histogram

Returns the number of bins by Scott's rule h = 3.5 * σ / (n^1/3).

ScreePlot - Class in smile.plot.swing

In multivariate statistics, a scree plot is a line plot of the eigenvalues of factors or principal components in an analysis.

ScreePlot(double[]) - Constructor for class smile.plot.swing.ScreePlot

Constructor.

sd - Variable in class smile.regression.GaussianProcessRegression.JointPrediction

The standard deviation of predictive distribution at query points.

sd - Variable in class smile.regression.GaussianProcessRegression

The standard deviation of responsible variable.

sd - Variable in class smile.validation.ClassificationValidations

The standard deviation of metrics.

sd - Variable in class smile.validation.RegressionValidations

The standard deviation of metrics.

sd() - Method in class smile.neighbor.lsh.HashValueParzenModel

Returns the standard deviation.

sd() - Method in class smile.stat.distribution.BinomialDistribution

sd() - Method in class smile.stat.distribution.ChiSquareDistribution

sd() - Method in interface smile.stat.distribution.Distribution

Returns the standard deviation of distribution.

sd() - Method in class smile.stat.distribution.EmpiricalDistribution

sd() - Method in class smile.stat.distribution.ExponentialDistribution

sd() - Method in class smile.stat.distribution.GammaDistribution

sd() - Method in class smile.stat.distribution.GaussianDistribution

sd() - Method in class smile.stat.distribution.GeometricDistribution

sd() - Method in class smile.stat.distribution.KernelDensity

sd() - Method in class smile.stat.distribution.LogisticDistribution

sd() - Method in class smile.stat.distribution.NegativeBinomialDistribution

sd() - Method in class smile.stat.distribution.PoissonDistribution

sd() - Method in class smile.stat.distribution.ShiftedGeometricDistribution

sd() - Method in class smile.stat.distribution.TDistribution

sd(double[]) - Static method in class smile.math.MathEx

Returns the standard deviation of an array.

sd(float[]) - Static method in class smile.math.MathEx

Returns the standard deviation of an array.

sd(int[]) - Static method in class smile.math.MathEx

Returns the standard deviation of an array.

search(double) - Method in class smile.interpolation.AbstractInterpolation

Given a value x, return a value j such that x is (insofar as possible) centered in the subrange xx[j..j+m-1], where xx is the stored data.

search(double[], double, List<Neighbor<double[], E>>) - Method in class smile.neighbor.KDTree

search(double[], double, List<Neighbor<double[], E>>) - Method in class smile.neighbor.LSH

search(double[], double, List<Neighbor<double[], E>>) - Method in class smile.neighbor.MPLSH

search(double[], double, List<Neighbor<double[], E>>, double, int) - Method in class smile.neighbor.MPLSH

Search the neighbors in the given radius of query object, i.e.

search(double[], int) - Method in class smile.neighbor.KDTree

search(double[], int) - Method in class smile.neighbor.LSH

search(double[], int) - Method in class smile.neighbor.MPLSH

search(double[], int, double, int) - Method in class smile.neighbor.MPLSH

Returns the approximate k-nearest neighbors.

search(String) - Method in interface smile.nlp.Corpus

Returns the iterator over the set of documents containing the given term.

search(String) - Method in class smile.nlp.SimpleCorpus

search(K, double, List<Neighbor<K, V>>) - Method in class smile.neighbor.BKTree

search(K, double, List<Neighbor<K, V>>) - Method in class smile.neighbor.CoverTree

search(K, double, List<Neighbor<K, V>>) - Method in class smile.neighbor.LinearSearch

search(K, double, List<Neighbor<K, V>>) - Method in interface smile.neighbor.RNNSearch

Retrieves the neighbors in a fixed radius of query object, i.e.

search(K, double, List<Neighbor<K, V>>) - Method in class smile.neighbor.SNLSH

search(K, int) - Method in class smile.neighbor.CoverTree

search(K, int) - Method in interface smile.neighbor.KNNSearch

Retrieves the k nearest neighbors to the query key.

search(K, int) - Method in class smile.neighbor.LinearSearch

search(K, int, List<Neighbor<K, V>>) - Method in class smile.neighbor.BKTree

Search the neighbors in the given radius of query object, i.e.

search(RelevanceRanker, String) - Method in interface smile.nlp.Corpus

Returns the iterator over the set of documents containing the given term in descending order of relevance.

search(RelevanceRanker, String) - Method in class smile.nlp.SimpleCorpus

search(RelevanceRanker, String[]) - Method in interface smile.nlp.Corpus

Returns the iterator over the set of documents containing (at least one of) the given terms in descending order of relevance.

search(RelevanceRanker, String[]) - Method in class smile.nlp.SimpleCorpus

SECOND - Enum constant in enum class smile.data.formula.DateFeature

The seconds represented by an integer from 0 to 59 in the usual manner.

seed(int, double[][]) - Static method in class smile.vq.NeuralGas

Selects random samples as initial neurons of Neural Gas.

seed(T[], T[], int[], ToDoubleBiFunction<T, T>) - Static method in class smile.clustering.PartitionClustering

Initialize cluster membership of input objects with K-Means++ algorithm.

seeds() - Static method in class smile.math.MathEx

Returns a stream of random numbers to be used as RNG seeds.

select(double[], int) - Static method in interface smile.sort.QuickSelect

Given k in [0, n-1], returns an array value from arr such that k array values are less than or equal to the one returned.

select(float[], int) - Static method in interface smile.sort.QuickSelect

Given k in [0, n-1], returns an array value from arr such that k array values are less than or equal to the one returned.

select(int...) - Method in interface smile.data.DataFrame

Returns a new DataFrame with selected columns.

select(int...) - Method in class smile.data.IndexDataFrame

select(int[], int) - Static method in interface smile.sort.QuickSelect

Given k in [0, n-1], returns an array value from arr such that k array values are less than or equal to the one returned.

select(String...) - Method in interface smile.data.DataFrame

Returns a new DataFrame with selected columns.

select(T[], int) - Static method in interface smile.sort.QuickSelect

Given k in [0, n-1], returns an array value from arr such that k array values are less than or equal to the one returned.

Selection - Interface in smile.gap

The way to select chromosomes from the population as parents to crossover.

sensitivity - Variable in class smile.validation.ClassificationMetrics

The sensitivity on validation data.

Sensitivity - Class in smile.validation.metric

Sensitivity or true positive rate (TPR) (also called hit rate, recall) is a statistical measures of the performance of a binary classification test.

Sensitivity() - Constructor for class smile.validation.metric.Sensitivity

SENT - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Sentence-break punctuation .

sentencePiece(String) - Static method in interface smile.llm.tokenizer.Tokenizer

Loads a SentencePiece model.

SentencePiece - Class in smile.llm.tokenizer

SentencePiece is an unsupervised text tokenizer by Google.

SentencePiece(String) - Constructor for class smile.llm.tokenizer.SentencePiece

Constructor.

SentenceSplitter - Interface in smile.nlp.tokenizer

A sentence splitter segments text into sentences (a string of words satisfying the grammatical rules of a language).

SequenceLabeler<T> - Interface in smile.sequence

A sequence labeler assigns a class label to each position of the sequence.

SequentialBlock - Class in smile.deep.layer

A block of sequential layers.

SequentialBlock() - Constructor for class smile.deep.layer.SequentialBlock

Constructor.

SequentialBlock(String) - Constructor for class smile.deep.layer.SequentialBlock

Constructor.

SequentialBlock(Layer...) - Constructor for class smile.deep.layer.SequentialBlock

Constructor.

set(int, double) - Method in class smile.math.Complex.Array

Sets the i-th element with a real value.

set(int, double) - Method in class smile.math.matrix.SparseMatrix

Sets the element at the storage index.

set(int, double) - Method in class smile.util.DoubleArrayList

Replaces the value at the specified position in this list with the specified value.

set(int, double) - Method in class smile.util.SparseArray

Sets or adds an entry.

set(int, float) - Method in class smile.math.matrix.fp32.SparseMatrix

Sets the element at the storage index.

set(int, int) - Method in class smile.util.IntArrayList

Replaces the value at the specified position in this list with the specified value.

set(int, int, double) - Method in class smile.math.matrix.BandMatrix

set(int, int, double) - Method in class smile.math.matrix.BigMatrix

set(int, int, double) - Method in class smile.math.matrix.IMatrix

Sets A[i,j] = x.

set(int, int, double) - Method in class smile.math.matrix.Matrix

set(int, int, double) - Method in class smile.math.matrix.SymmMatrix

set(int, int, double) - Method in class smile.util.Array2D

Sets A[i, j].

set(int, int, float) - Method in class smile.math.matrix.fp32.BandMatrix

set(int, int, float) - Method in class smile.math.matrix.fp32.IMatrix

Sets A[i,j] = x.

set(int, int, float) - Method in class smile.math.matrix.fp32.Matrix

set(int, int, float) - Method in class smile.math.matrix.fp32.SparseMatrix

set(int, int, float) - Method in class smile.math.matrix.fp32.SymmMatrix

set(int, int, int) - Method in class smile.util.IntArray2D

Sets A[i, j].

set(int, Complex) - Method in class smile.math.Complex.Array

Sets the i-th element.

set(BigMatrix) - Method in class smile.math.matrix.BigMatrix

Sets the matrix value.

set(Matrix) - Method in class smile.math.matrix.fp32.Matrix

Sets the matrix value.

set(Matrix) - Method in class smile.math.matrix.Matrix

Sets the matrix value.

setAnchor(String) - Method in interface smile.nlp.AnchorText

Sets the anchor text.

setAnchor(String) - Method in class smile.nlp.SimpleText

Sets the anchor text.

setAxisLabel(int, String) - Method in class smile.plot.swing.Canvas

Sets the label/legend of an axis.

setAxisLabels(String...) - Method in class smile.plot.swing.Canvas

Sets the labels/legends of axes.

setBound(double[], double[]) - Method in class smile.plot.swing.Base

Sets the axis bounds without applying the extending heuristic.

setBound(double[], double[]) - Method in class smile.plot.swing.Canvas

Extend lower and upper bounds.

setClipNorm(double) - Method in class smile.base.mlp.MultilayerPerceptron

Sets the gradient clipping norm.

setClipValue(double) - Method in class smile.base.mlp.MultilayerPerceptron

Sets the gradient clipping value.

setColor(Color) - Method in class smile.plot.swing.Graphics

Set the color.

setDefaultDevice() - Method in class smile.deep.tensor.Device

Sets Tensor to be allocated on this device.

setDescription(String) - Method in class smile.swing.FileChooser.SimpleFileFilter

Sets the human readable description of this filter.

setEdgeAge(Neuron, int) - Method in class smile.vq.hebb.Neuron

Sets the age of edge.

setFocusBorder(Border) - Method in class smile.swing.table.ButtonCellRenderer

The foreground color of the button when the cell has focus

setFont(Font) - Method in class smile.plot.swing.Graphics

Set the font.

setFrameVisible(boolean) - Method in class smile.plot.swing.Axis

Set the visibility of the frame grid lines and their labels.

setGraphics(Graphics2D, int, int) - Method in class smile.plot.swing.Graphics

Set the Java2D graphics object.

setGridVisible(boolean) - Method in class smile.plot.swing.Axis

Set the visibility of the grid lines and their labels.

setLabel(String) - Method in class smile.plot.swing.Axis

Sets the label.

setLearningRate(double) - Method in class smile.classification.LogisticRegression

Sets the learning rate of stochastic gradient descent.

setLearningRate(double) - Method in class smile.classification.Maxent

Sets the learning rate of stochastic gradient descent.

setLearningRate(double) - Method in class smile.classification.SparseLogisticRegression

Sets the learning rate of stochastic gradient descent.

setLearningRate(double) - Method in class smile.deep.Optimizer

Sets the learning rate.

setLearningRate(TimeFunction) - Method in class smile.base.mlp.MultilayerPerceptron

Sets the learning rate.

setLearningRateSchedule(TimeFunction) - Method in class smile.deep.Model

Sets the learning rate schedule.

setLegendVisible(boolean) - Method in class smile.plot.swing.Canvas

Sets if legends are visible.

setLocalSearchSteps(int) - Method in class smile.gap.GeneticAlgorithm

Sets the number of iterations of local search for Lamarckian algorithm.

setMargin(double) - Method in class smile.plot.swing.Canvas

Sets the size of margin in [0.0, 0.3] on each side.

setMnemonic(int) - Method in class smile.swing.table.ButtonCellRenderer

The mnemonic to activate the button when the cell has focus

setMomentum(TimeFunction) - Method in class smile.base.mlp.MultilayerPerceptron

Sets the momentum factor.

setPage(int) - Method in class smile.swing.table.PageTableModel

Moves to specific page and fire a data changed (all rows).

setPageSize(int) - Method in class smile.swing.table.PageTableModel

Sets the page size.

setPaint(Paint) - Method in class smile.plot.swing.Graphics

Set the paint object.

setParameters(Properties) - Method in class smile.base.mlp.MultilayerPerceptron

Sets MLP hyper-parameters such as learning rate, weight decay, momentum, RMSProp, etc.

setProb(PrZ[]) - Method in class smile.neighbor.lsh.Probe

Calculate the probability of the probe.

setRMSProp(double, double) - Method in class smile.base.mlp.MultilayerPerceptron

Sets RMSProp parameters.

setRotation(double) - Method in class smile.plot.swing.Axis

Sets the rotation degree of tick strings.

setSeed(int) - Method in class smile.math.random.MersenneTwister

Sets the seed of random numbers.

setSeed(int[]) - Method in class smile.math.random.MersenneTwister

Sets the seed of random numbers.

setSeed(long) - Static method in class smile.math.MathEx

Initialize the random number generator with a seed.

setSeed(long) - Method in class smile.math.random.MersenneTwister

setSeed(long) - Method in class smile.math.random.MersenneTwister64

setSeed(long) - Method in interface smile.math.random.RandomNumberGenerator

Initialize the random generator with a seed.

setSeed(long) - Method in class smile.math.Random

Initialize the random generator with a seed.

setSeed(long) - Method in class smile.math.random.UniversalGenerator

setSeed(long[]) - Method in class smile.math.random.MersenneTwister64

Sets the seed of random numbers.

setSelectedFont(Font) - Method in class smile.swing.FontChooser

Set the selected font.

setSelectedFontFamily(String) - Method in class smile.swing.FontChooser

Set the family name of the selected font.

setSelectedFontSize(int) - Method in class smile.swing.FontChooser

Set the size of the selected font.

setSelectedFontStyle(int) - Method in class smile.swing.FontChooser

Set the style of the selected font.

setStroke(Stroke) - Method in class smile.plot.swing.Graphics

Set the stroke.

setTicks(String[], double[]) - Method in class smile.plot.swing.Axis

Add a label to the axis at given location.

setTickVisible(boolean) - Method in class smile.plot.swing.Axis

Set the visibility of the axis label.

setTitle(String) - Method in class smile.plot.swing.Canvas

Set the main title of canvas.

setTitleColor(Color) - Method in class smile.plot.swing.Canvas

Set the color for title.

setTitleFont(Font) - Method in class smile.plot.swing.Canvas

Set the font for title.

setValue(Object) - Method in class smile.swing.table.ByteArrayCellRenderer

setValue(Object) - Method in class smile.swing.table.DateCellRenderer

setValue(Object) - Method in class smile.swing.table.DoubleArrayCellRenderer

setValue(Object) - Method in class smile.swing.table.FloatArrayCellRenderer

setValue(Object) - Method in class smile.swing.table.FontCellRenderer

setValue(Object) - Method in class smile.swing.table.IntegerArrayCellRenderer

setValue(Object) - Method in class smile.swing.table.LongArrayCellRenderer

setValue(Object) - Method in class smile.swing.table.NumberCellRenderer

setValue(Object) - Method in class smile.swing.table.ShortArrayCellRenderer

setWeight(int, int, double) - Method in class smile.graph.AdjacencyList

setWeight(int, int, double) - Method in class smile.graph.AdjacencyMatrix

setWeight(int, int, double) - Method in interface smile.graph.Graph

Sets the weight assigned to a given edge.

setWeightDecay(double) - Method in class smile.base.mlp.MultilayerPerceptron

Sets the weight decay factor.

SGD - Class in smile.base.mlp.optimizer

Stochastic gradient descent (with momentum) optimizer.

SGD() - Constructor for class smile.base.mlp.optimizer.SGD

Constructor.

SGD(TimeFunction) - Constructor for class smile.base.mlp.optimizer.SGD

Constructor.

SGD(TimeFunction, TimeFunction) - Constructor for class smile.base.mlp.optimizer.SGD

Constructor.

SGD(Model, double) - Static method in class smile.deep.Optimizer

Returns a stochastic gradient descent optimizer without momentum.

SGD(Model, double, double, double, double, boolean) - Static method in class smile.deep.Optimizer

Returns a stochastic gradient descent optimizer with momentum.

shap(Stream<T>) - Method in interface smile.feature.importance.SHAP

Returns the average of absolute SHAP values over a data set.

shap(DataFrame) - Method in class smile.base.cart.CART

Returns the average of absolute SHAP values over a data frame.

shap(DataFrame) - Method in class smile.classification.GradientTreeBoost

Returns the average of absolute SHAP values over a data frame.

shap(DataFrame) - Method in interface smile.feature.importance.TreeSHAP

Returns the average of absolute SHAP values over a data frame.

shap(Tuple) - Method in class smile.base.cart.CART

shap(Tuple) - Method in class smile.classification.GradientTreeBoost

shap(Tuple) - Method in interface smile.feature.importance.TreeSHAP

shap(T) - Method in interface smile.feature.importance.SHAP

Returns the SHAP values.

SHAP<T> - Interface in smile.feature.importance

SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model.

shape() - Method in class smile.deep.tensor.Tensor

Returns the shape of the tensor.

shape(String) - Method in class smile.plot.vega.Mark

Sets the shape of the point marks.

Shape - Class in smile.plot.swing

Abstract rendering object in a PlotCanvas.

Shape() - Constructor for class smile.plot.swing.Shape

Constructor.

Shape(Color) - Constructor for class smile.plot.swing.Shape

Constructor.

ShellSort - Interface in smile.sort

Shell sort is a generalization of insertion sort.

ShepardInterpolation - Class in smile.interpolation

Shepard interpolation is a special case of normalized radial basis function interpolation if the function φ(r) goes to infinity as r → 0, and is finite for r > 0.

ShepardInterpolation(double[][], double[]) - Constructor for class smile.interpolation.ShepardInterpolation

Constructor.

ShepardInterpolation(double[][], double[], double) - Constructor for class smile.interpolation.ShepardInterpolation

Constructor.

ShepardInterpolation1D - Class in smile.interpolation

Shepard interpolation is a special case of normalized radial basis function interpolation if the function φ(r) goes to infinity as r → 0, and is finite for r > 0.

ShepardInterpolation1D(double[], double[]) - Constructor for class smile.interpolation.ShepardInterpolation1D

Constructor.

ShepardInterpolation1D(double[], double[], double) - Constructor for class smile.interpolation.ShepardInterpolation1D

Constructor.

ShepardInterpolation2D - Class in smile.interpolation

Shepard interpolation is a special case of normalized radial basis function interpolation if the function φ(r) goes to infinity as r → 0, and is finite for r > 0.

ShepardInterpolation2D(double[], double[], double[]) - Constructor for class smile.interpolation.ShepardInterpolation2D

Constructor.

ShepardInterpolation2D(double[], double[], double[], double) - Constructor for class smile.interpolation.ShepardInterpolation2D

Constructor.

shift() - Method in class smile.neighbor.lsh.Probe

This operation shifts to the right the last nonzero component if it is equal to one and if it is not the last one.

ShiftedGeometricDistribution - Class in smile.stat.distribution

The "shifted" geometric distribution is a discrete probability distribution of the number of failures before the first success, supported on the set {0, 1, 2, 3, …}.

ShiftedGeometricDistribution(double) - Constructor for class smile.stat.distribution.ShiftedGeometricDistribution

Constructor.

Short - Enum constant in enum class smile.data.type.DataType.ID

Short type ID.

ShortArrayCellRenderer - Class in smile.swing.table

Short array renderer in JTable.

ShortArrayCellRenderer() - Constructor for class smile.swing.table.ShortArrayCellRenderer

Constructor.

ShortArrayType - Static variable in class smile.data.type.DataTypes

Short Array data type.

ShortObjectType - Static variable in class smile.data.type.DataTypes

Short Object data type.

ShortType - Class in smile.data.type

Short data type.

ShortType - Static variable in class smile.data.type.DataTypes

Short data type.

shortValue() - Method in class smile.deep.tensor.Tensor

Returns the short value when the tensor holds a single value.

shortVector(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

shortVector(int) - Method in class smile.data.IndexDataFrame

shortVector(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

shortVector(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

ShortVector - Interface in smile.data.vector

An immutable short vector.

show() - Method in class smile.plot.swing.Headless

show() - Method in class smile.plot.vega.VegaLite

Displays the plot with the default browser.

show(boolean) - Method in class smile.plot.vega.VegaLite

Displays the plot with the default browser.

showDialog(Component) - Method in class smile.swing.FontChooser

Show font selection dialog.

SI - Enum constant in enum class smile.math.matrix.ARPACK.AsymmOption

The eigenvalues of smallest imaginary part.

SI - Enum constant in enum class smile.math.matrix.fp32.ARPACK.AsymmOption

The eigenvalues of smallest imaginary part.

SIB - Class in smile.clustering

The Sequential Information Bottleneck algorithm.

SIB(double, double[][], int[]) - Constructor for class smile.clustering.SIB

Constructor.

Side - Enum Class in smile.math.blas

The flag if the symmetric matrix A appears on the left or right in the matrix-matrix operation.

siftDown(double[], int, int) - Static method in interface smile.sort.Sort

To restore the max-heap condition when a node's priority is decreased.

siftDown(float[], int, int) - Static method in interface smile.sort.Sort

To restore the max-heap condition when a node's priority is decreased.

siftDown(int[], int, int) - Static method in interface smile.sort.Sort

To restore the max-heap condition when a node's priority is decreased.

siftDown(T[], int, int) - Static method in interface smile.sort.Sort

To restore the max-heap condition when a node's priority is decreased.

siftUp(double[], int) - Static method in interface smile.sort.Sort

To restore the max-heap condition when a node's priority is increased.

siftUp(float[], int) - Static method in interface smile.sort.Sort

To restore the max-heap condition when a node's priority is increased.

siftUp(int[], int) - Static method in interface smile.sort.Sort

To restore the max-heap condition when a node's priority is increased.

siftUp(T[], int) - Static method in interface smile.sort.Sort

To restore the max-heap condition when a node's priority is increased.

sigma - Variable in class smile.stat.distribution.GaussianDistribution

The standard deviation.

sigma - Variable in class smile.stat.distribution.LogNormalDistribution

The standard deviation of normal distribution.

sigma - Variable in class smile.stat.distribution.MultivariateGaussianDistribution

The covariance matrix.

sigma() - Method in class smile.math.kernel.PearsonKernel

Returns Pearson width.

sigmoid() - Static method in interface smile.base.mlp.activation.ActivationFunction

Returns the logistic sigmoid function: sigmoid(v)=1/(1+exp(-v)).

sigmoid() - Static method in interface smile.base.mlp.ActivationFunction

Logistic sigmoid function: sigmoid(v)=1/(1+exp(-v)).

sigmoid(double) - Static method in class smile.math.MathEx

Logistic sigmoid function 1 / (1 + exp(-x)).

sigmoid(int) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with sigmoid activation function.

sigmoid(int, double) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with sigmoid activation function.

sigmoid(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with sigmoid activation function.

Sigmoid - Class in smile.base.mlp.activation

Logistic sigmoid function: sigmoid(v)=1/(1+exp(-v)).

Sigmoid - Class in smile.deep.activation

Sigmoid activation function.

Sigmoid() - Constructor for class smile.base.mlp.activation.Sigmoid

Constructor.

Sigmoid(boolean) - Constructor for class smile.deep.activation.Sigmoid

Constructor.

SIGMOID - Enum constant in enum class smile.base.mlp.OutputFunction

Logistic sigmoid function: sigmoid(v)=1/(1+exp(-v)).

sign(String) - Static method in interface smile.data.formula.Terms

The sign(x) term.

sign(Term) - Static method in interface smile.data.formula.Terms

The sign(x) term.

SignalNoiseRatio - Class in smile.feature.selection

The signal-to-noise (S2N) metric ratio is a univariate feature ranking metric, which can be used as a feature selection criterion for binary classification problems.

SignalNoiseRatio(String, double) - Constructor for class smile.feature.selection.SignalNoiseRatio

Constructor.

significance(double) - Static method in interface smile.stat.Hypothesis

Returns the significance code of p-value.

signum(String) - Static method in interface smile.data.formula.Terms

The signum(x) term.

signum(Term) - Static method in interface smile.data.formula.Terms

The signum(x) term.

silu(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with SiLU activation function.

silu(int, int, double) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with SiLU activation function.

SiLU - Class in smile.deep.activation

Sigmoid Linear Unit activation function.

SiLU(boolean) - Constructor for class smile.deep.activation.SiLU

Constructor.

SimHash<T> - Interface in smile.hash

SimHash is a technique for quickly estimating how similar two sets are.

SimpleCorpus - Class in smile.nlp

An in-memory text corpus.

SimpleCorpus() - Constructor for class smile.nlp.SimpleCorpus

Constructor.

SimpleCorpus(SentenceSplitter, Tokenizer, StopWords, Punctuations) - Constructor for class smile.nlp.SimpleCorpus

Constructor.

SimpleDictionary - Class in smile.nlp.dictionary

A simple implementation of dictionary interface.

SimpleDictionary(String) - Constructor for class smile.nlp.dictionary.SimpleDictionary

Constructor.

SimpleFileFilter(String, String) - Constructor for class smile.swing.FileChooser.SimpleFileFilter

Creates a file filter that accepts the given file type.

SimpleFileFilter(String, String...) - Constructor for class smile.swing.FileChooser.SimpleFileFilter

Creates a file filter from the given string array and description.

SimpleFileFilter(String, Collection<String>) - Constructor for class smile.swing.FileChooser.SimpleFileFilter

Creates a file filter from the given string array and description.

SimpleImputer - Class in smile.feature.imputation

Simple algorithm replaces missing values with the constant value along each column.

SimpleImputer(Map<String, Object>) - Constructor for class smile.feature.imputation.SimpleImputer

Constructor.

SimpleNormalizer - Class in smile.nlp.normalizer

A baseline normalizer for processing Unicode text.

SimpleParagraphSplitter - Class in smile.nlp.tokenizer

This is a simple paragraph splitter.

SimpleSentenceSplitter - Class in smile.nlp.tokenizer

This is a simple sentence splitter for English.

SimpleText - Class in smile.nlp

A list-of-words representation of documents.

SimpleText(String, String, String, String[]) - Constructor for class smile.nlp.SimpleText

Constructor.

SimpleTokenizer - Class in smile.nlp.tokenizer

A word tokenizer that tokenizes English sentences with some differences from TreebankWordTokenizer, notably on handling not-contractions.

SimpleTokenizer() - Constructor for class smile.nlp.tokenizer.SimpleTokenizer

Constructor.

SimpleTokenizer(boolean) - Constructor for class smile.nlp.tokenizer.SimpleTokenizer

Constructor.

sin() - Method in class smile.deep.tensor.Tensor

Returns a new tensor with the sine of the elements of input.

sin() - Method in class smile.math.Complex

Returns the complex sine.

sin(String) - Static method in interface smile.data.formula.Terms

The sin(x) term.

sin(Term) - Static method in interface smile.data.formula.Terms

The sin(x) term.

sin_() - Method in class smile.deep.tensor.Tensor

Computes the sine of the elements of input in place.

SINGLE_LINE - Enum constant in enum class smile.io.JSON.Mode

One JSON object per line.

SINGLE_POINT - Enum constant in enum class smile.gap.Crossover

Single point crossover - one crossover point is selected, binary string from beginning of chromosome to the crossover point is copied from one parent, the rest is copied from the second parent.

SingleLinkage - Class in smile.clustering.linkage

Single linkage.

SingleLinkage(double[][]) - Constructor for class smile.clustering.linkage.SingleLinkage

Constructor.

SingleLinkage(int, float[]) - Constructor for class smile.clustering.linkage.SingleLinkage

Constructor.

sinh(String) - Static method in interface smile.data.formula.Terms

The sinh(x) term.

sinh(Term) - Static method in interface smile.data.formula.Terms

The sinh(x) term.

size - Variable in class smile.base.cart.LeafNode

The number of samples in the node.

size - Variable in class smile.clustering.PartitionClustering

The number of observations in each cluster.

size - Variable in class smile.validation.ClassificationMetrics

The validation data size.

size - Variable in class smile.validation.RegressionMetrics

The validation data size.

size() - Method in class smile.anomaly.IsolationForest

Returns the number of trees in the model.

size() - Method in class smile.association.FPGrowth

Returns the number transactions in the database.

size() - Method in class smile.association.FPTree

Returns the number transactions in the database.

size() - Method in class smile.base.cart.CART

Returns the number of nodes in the tree.

size() - Method in class smile.base.cart.InternalNode

size() - Method in class smile.base.cart.LeafNode

size() - Method in interface smile.base.cart.Node

Returns the number of samples in the node.

size() - Method in class smile.classification.AdaBoost

Returns the number of trees in the model.

size() - Method in class smile.classification.GradientTreeBoost

Returns the number of trees in the model.

size() - Method in class smile.classification.RandomForest

Returns the number of trees in the model.

size() - Method in class smile.clustering.linkage.Linkage

Returns the proximity matrix size.

size() - Method in interface smile.data.DataFrame

Returns the number of rows.

size() - Method in interface smile.data.Dataset

Returns the number of elements in this collection.

size() - Method in class smile.data.formula.FactorInteraction

Returns the number of factors in the interaction.

size() - Method in class smile.data.IndexDataFrame

size() - Method in class smile.data.measure.CategoricalMeasure

Returns the number of levels.

size() - Method in interface smile.data.vector.BaseVector

Returns the number of elements in the vector.

size() - Method in interface smile.deep.Dataset

Returns the size of dataset.

size() - Method in class smile.math.matrix.BandMatrix

size() - Method in class smile.math.matrix.BigMatrix

size() - Method in class smile.math.matrix.fp32.BandMatrix

size() - Method in class smile.math.matrix.fp32.IMatrix

Returns the number of stored matrix elements.

size() - Method in class smile.math.matrix.fp32.Matrix

size() - Method in class smile.math.matrix.fp32.SparseMatrix

size() - Method in class smile.math.matrix.fp32.SymmMatrix

size() - Method in class smile.math.matrix.IMatrix

Returns the number of stored matrix elements.

size() - Method in class smile.math.matrix.Matrix

size() - Method in class smile.math.matrix.SparseMatrix

size() - Method in class smile.math.matrix.SymmMatrix

size() - Method in interface smile.nlp.Corpus

Returns the number of words in the corpus.

size() - Method in interface smile.nlp.dictionary.Dictionary

Returns the number of words in this dictionary.

size() - Method in enum class smile.nlp.dictionary.EnglishDictionary

size() - Method in class smile.nlp.dictionary.EnglishPunctuations

size() - Method in enum class smile.nlp.dictionary.EnglishStopWords

size() - Method in class smile.nlp.dictionary.SimpleDictionary

size() - Method in class smile.nlp.SimpleCorpus

size() - Method in class smile.nlp.SimpleText

size() - Method in interface smile.nlp.TextTerms

Returns the number of words.

size() - Method in class smile.nlp.Trie

Returns the number of entries.

size() - Method in class smile.regression.GradientTreeBoost

Returns the number of trees in the model.

size() - Method in class smile.regression.RandomForest

Returns the number of trees in the model.

size() - Method in class smile.sort.HeapSelect

Returns the number of objects that have been added into heap.

size() - Method in class smile.stat.distribution.DiscreteMixture

Returns the number of components in the mixture.

size() - Method in class smile.stat.distribution.Mixture

Returns the number of components in the mixture.

size() - Method in class smile.stat.distribution.MultivariateMixture

Returns the number of components in the mixture.

size() - Method in class smile.util.DoubleArrayList

Returns the number of values in the list.

size() - Method in class smile.util.IntArrayList

Returns the number of values in the list.

size() - Method in class smile.util.IntDoubleHashMap

Returns the number of key-value mappings in this map.

size() - Method in class smile.util.IntHashSet

Returns the number of elements in this set.

size() - Method in class smile.util.IntSet

Returns the number of values.

size() - Method in class smile.util.SparseArray

Returns the number of nonzero entries.

size() - Method in class smile.vision.ImageDataset

size(int) - Method in class smile.deep.tensor.Tensor

Returns the size of given dimension.

size(int) - Method in class smile.plot.vega.Mark

Sets the size of the point marks.

SKY_BLUE - Static variable in interface smile.plot.swing.Palette

SLATE_BLUE - Static variable in interface smile.plot.swing.Palette

SLATE_GRAY - Static variable in interface smile.plot.swing.Palette

slice(double[], int[]) - Static method in class smile.math.MathEx

Returns a slice of data for given indices.

slice(float[], int[]) - Static method in class smile.math.MathEx

Returns a slice of data for given indices.

slice(int[], int[]) - Static method in class smile.math.MathEx

Returns a slice of data for given indices.

slice(int, int) - Method in interface smile.data.DataFrame

Copies the specified range into a new data frame.

slice(int, int) - Method in record class smile.util.Bytes

Returns a copy of byte string slice.

slice(E[], int[]) - Static method in class smile.math.MathEx

Returns a slice of data for given indices.

slice(Integer, Integer) - Static method in class smile.deep.tensor.Index

Returns the slice index for [start, end) with step 1.

slice(Integer, Integer, Integer) - Static method in class smile.deep.tensor.Index

Returns the slice index for [start, end) with step 1.

slice(Long, Long) - Static method in class smile.deep.tensor.Index

Returns the slice index for [start, end) with step 1.

slice(Long, Long, Long) - Static method in class smile.deep.tensor.Index

Returns the slice index for [start, end) with the given step.

slices() - Method in class smile.plot.swing.Axis

Returns the number of slices in linear scale.

SM - Enum constant in enum class smile.math.matrix.ARPACK.AsymmOption

The eigenvalues smallest in magnitude.

SM - Enum constant in enum class smile.math.matrix.ARPACK.SymmOption

The eigenvalues smallest in magnitude.

SM - Enum constant in enum class smile.math.matrix.fp32.ARPACK.AsymmOption

The eigenvalues smallest in magnitude.

SM - Enum constant in enum class smile.math.matrix.fp32.ARPACK.SymmOption

The eigenvalues smallest in magnitude.

smile.anomaly - package smile.anomaly

Anomaly detection is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data.

smile.association - package smile.association

Frequent item set mining and association rule mining.

smile.base.cart - package smile.base.cart

Classification and regression tree base package.

smile.base.mlp - package smile.base.mlp

Multilayer perceptron neural network base package.

smile.base.mlp.activation - package smile.base.mlp.activation

smile.base.mlp.optimizer - package smile.base.mlp.optimizer

smile.base.rbf - package smile.base.rbf

RBF network base package.

smile.base.svm - package smile.base.svm

Support vector machine base package.

smile.classification - package smile.classification

Classification algorithms.

smile.clustering - package smile.clustering

Clustering analysis.

smile.clustering.linkage - package smile.clustering.linkage

Cluster dissimilarity measures.

smile.data - package smile.data

Data and attribute encapsulation classes.

smile.data.formula - package smile.data.formula

The formula interface symbolically specifies the predictors and the response.

smile.data.measure - package smile.data.measure

Level of measurement or scale of measure.

smile.data.transform - package smile.data.transform

Data transformations.

smile.data.type - package smile.data.type

Data types.

smile.data.vector - package smile.data.vector

Immutable named vectors.

smile.deep - package smile.deep

Deep learning.

smile.deep.activation - package smile.deep.activation

Activation functions.

smile.deep.layer - package smile.deep.layer

Neural network layers.

smile.deep.metric - package smile.deep.metric

Model validation metrics.

smile.deep.tensor - package smile.deep.tensor

A tensor is a multi-dimensional array.

smile.feature.extraction - package smile.feature.extraction

Feature extraction.

smile.feature.importance - package smile.feature.importance

Feature importance.

smile.feature.imputation - package smile.feature.imputation

Missing value imputation.

smile.feature.selection - package smile.feature.selection

Feature selection.

smile.feature.transform - package smile.feature.transform

Feature transformations.

smile.gap - package smile.gap

Genetic algorithm and programming.

smile.glm - package smile.glm

Generalized linear models.

smile.glm.model - package smile.glm.model

The error distribution models.

smile.graph - package smile.graph

Graphs are mathematical structures used to model pairwise relations between objects from a certain collection.

smile.hash - package smile.hash

Hashing functions.

smile.hpo - package smile.hpo

Hyperparameter optimization.

smile.ica - package smile.ica

Independent Component Analysis (ICA).

smile.interpolation - package smile.interpolation

Interpolation is the process of constructing a function that takes on specified values at specified points.

smile.interpolation.variogram - package smile.interpolation.variogram

Variogram functions.

smile.io - package smile.io

Interfaces to read/write a Dataset.

smile.llm - package smile.llm

Large language models.

smile.llm.tokenizer - package smile.llm.tokenizer

LLM Tokenization.

smile.manifold - package smile.manifold

Manifold learning finds a low-dimensional basis for describing high-dimensional data.

smile.math - package smile.math

Basic mathematical functions, complex, differentiable function interfaces, random number generators, unconstrained optimization, and raw data type (int and double) array lists, etc.

smile.math.blas - package smile.math.blas

BLAS and LAPACK interfaces.

smile.math.blas.openblas - package smile.math.blas.openblas

OpenBLAS library.

smile.math.distance - package smile.math.distance

Distance and metric measures.

smile.math.kernel - package smile.math.kernel

Mercer kernels.

smile.math.matrix - package smile.math.matrix

Matrix interface, dense and sparse (band or irregular) matrix encapsulation classes, LU, QR, Cholesky, SVD and eigen decompositions, etc.

smile.math.matrix.fp32 - package smile.math.matrix.fp32

Single-precision (32-bit) matrix.

smile.math.random - package smile.math.random

High quality random number generators as a replacement of the standard Random class of Java system.

smile.math.rbf - package smile.math.rbf

Radial basis functions.

smile.math.special - package smile.math.special

Special mathematical functions including beta, erf, and gamma.

smile.neighbor - package smile.neighbor

Nearest neighbor search.

smile.neighbor.lsh - package smile.neighbor.lsh

LSH internal classes.

smile.nlp - package smile.nlp

Natural language processing.

smile.nlp.collocation - package smile.nlp.collocation

Collocation finding algorithms.

smile.nlp.dictionary - package smile.nlp.dictionary

Common dictionaries such as stop words, punctuation, common English words, etc.

smile.nlp.embedding - package smile.nlp.embedding

Word embedding.

smile.nlp.keyword - package smile.nlp.keyword

Keyword extraction.

smile.nlp.normalizer - package smile.nlp.normalizer

Text normalization.

smile.nlp.pos - package smile.nlp.pos

Part-of-speech taggers.

smile.nlp.relevance - package smile.nlp.relevance

Term-document relevance ranking algorithms.

smile.nlp.stemmer - package smile.nlp.stemmer

English word stemmer algorithms.

smile.nlp.tokenizer - package smile.nlp.tokenizer

Sentence splitter and word tokenizer.

smile.plot.swing - package smile.plot.swing

Mathematical and statistical plots.

smile.plot.vega - package smile.plot.vega

Declarative data visualization.

smile.regression - package smile.regression

Regression analysis.

smile.sequence - package smile.sequence

Learning algorithms for sequence data.

smile.sort - package smile.sort

Sorting algorithms.

smile.stat - package smile.stat

Probability distributions and statistical hypothesis tests.

smile.stat.distribution - package smile.stat.distribution

Probability distributions.

smile.stat.hypothesis - package smile.stat.hypothesis

Statistical hypothesis tests.

smile.swing - package smile.swing

Enhanced and additional Swing components (FileChooser, FontChooser, Table, Button, AlphaIcon, and Printer).

smile.swing.table - package smile.swing.table

Enhancement to Swing JTable and cell components.

smile.taxonomy - package smile.taxonomy

A taxonomy is a tree of terms (concepts) where leaves must be named but intermediary nodes can be anonymous.

smile.timeseries - package smile.timeseries

Time series analysis.

smile.util - package smile.util

Utility functions.

smile.validation - package smile.validation

Model validation and selection.

smile.validation.metric - package smile.validation.metric

Model validation metrics.

smile.vision - package smile.vision

Computer vision models.

smile.vision.layer - package smile.vision.layer

Neural network layers for computer vision tasks.

smile.vision.transform - package smile.vision.transform

Image transformations.

smile.vq - package smile.vq

Vector quantization is a lossy compression technique used in speech and image coding.

smile.vq.hebb - package smile.vq.hebb

Hebbian theory is a neuroscientific theory claiming that an increase in synaptic efficacy arises from a presynaptic cell's repeated and persistent stimulation of a postsynaptic cell.

smile.wavelet - package smile.wavelet

Discrete wavelet transform (DWT).

smoothness() - Method in class smile.math.kernel.Matern

Returns the smoothness of kernel.

SNLSH<K,V> - Class in smile.neighbor

Locality-Sensitive Hashing for Signatures.

SNLSH(int, SimHash<K>) - Constructor for class smile.neighbor.SNLSH

Constructor.

soft() - Method in class smile.classification.AdaBoost

soft() - Method in interface smile.classification.Classifier

Returns true if this is a soft classifier that can estimate the posteriori probabilities of classification.

soft() - Method in class smile.classification.DecisionTree

soft() - Method in class smile.classification.DiscreteNaiveBayes

soft() - Method in class smile.classification.GradientTreeBoost

soft() - Method in class smile.classification.KNN

soft() - Method in class smile.classification.LDA

soft() - Method in class smile.classification.LogisticRegression

soft() - Method in class smile.classification.Maxent

soft() - Method in class smile.classification.MLP

soft() - Method in class smile.classification.NaiveBayes

soft() - Method in class smile.classification.OneVersusOne

soft() - Method in class smile.classification.OneVersusRest

soft() - Method in class smile.classification.QDA

soft() - Method in class smile.classification.RandomForest

soft() - Method in class smile.classification.SparseLogisticRegression

softmax() - Static method in interface smile.base.mlp.activation.ActivationFunction

Returns the softmax activation function for multi-class output layer.

softmax(double[]) - Static method in class smile.math.MathEx

The softmax function without overflow.

softmax(double[], int) - Static method in class smile.math.MathEx

The softmax function without overflow.

softmax(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with softmax activation function.

Softmax - Class in smile.base.mlp.activation

Softmax for multi-class cross entropy objection function.

Softmax - Class in smile.deep.activation

Softmax activation function.

Softmax() - Constructor for class smile.base.mlp.activation.Softmax

Constructor.

Softmax() - Constructor for class smile.deep.activation.Softmax

Constructor.

SOFTMAX - Enum constant in enum class smile.base.mlp.OutputFunction

Softmax for multi-class cross entropy objection function.

softShrink(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with soft shrink activation function.

SoftShrink - Class in smile.deep.activation

Soft Shrink activation function.

SoftShrink() - Constructor for class smile.deep.activation.SoftShrink

Constructor.

SoftShrink(double) - Constructor for class smile.deep.activation.SoftShrink

Constructor.

SOLID - Enum constant in enum class smile.plot.swing.Line.Style

solve(double[]) - Method in class smile.math.matrix.BandMatrix.Cholesky

Solves the linear system A * x = b.

solve(double[]) - Method in class smile.math.matrix.BandMatrix.LU

Solve A * x = b.

solve(double[]) - Method in class smile.math.matrix.BigMatrix.Cholesky

Solves the linear system A * x = b.

solve(double[]) - Method in class smile.math.matrix.BigMatrix.LU

Solve A * x = b.

solve(double[]) - Method in class smile.math.matrix.BigMatrix.QR

Solves the least squares min || B - A*X ||.

solve(double[]) - Method in class smile.math.matrix.BigMatrix.SVD

Solves the least squares min || B - A*X ||.

solve(double[]) - Method in class smile.math.matrix.Matrix.Cholesky

Solves the linear system A * x = b.

solve(double[]) - Method in class smile.math.matrix.Matrix.LU

Solve A * x = b.

solve(double[]) - Method in class smile.math.matrix.Matrix.QR

Solves the least squares min || B - A*X ||.

solve(double[]) - Method in class smile.math.matrix.Matrix.SVD

Solves the least squares min || B - A*X ||.

solve(double[]) - Method in class smile.math.matrix.SymmMatrix.BunchKaufman

Solve A * x = b.

solve(double[]) - Method in class smile.math.matrix.SymmMatrix.Cholesky

Solves the linear system A * x = b.

solve(double[], double[]) - Method in class smile.math.matrix.IMatrix

Solves A * x = b by iterative biconjugate gradient method with Jacobi preconditioner matrix.

solve(double[], double[], double[], double[]) - Static method in class smile.math.MathEx

Solve the tridiagonal linear set which is of diagonal dominance |b_i| > |a_i| + |c_i|.

solve(double[], double[], IMatrix.Preconditioner, double, int, int) - Method in class smile.math.matrix.IMatrix

Solves A * x = b by iterative biconjugate gradient method.

solve(float[]) - Method in class smile.math.matrix.fp32.BandMatrix.Cholesky

Solves the linear system A * x = b.

solve(float[]) - Method in class smile.math.matrix.fp32.BandMatrix.LU

Solve A * x = b.

solve(float[]) - Method in class smile.math.matrix.fp32.Matrix.Cholesky

Solves the linear system A * x = b.

solve(float[]) - Method in class smile.math.matrix.fp32.Matrix.LU

Solve A * x = b.

solve(float[]) - Method in class smile.math.matrix.fp32.Matrix.QR

Solves the least squares min || B - A*X ||.

solve(float[]) - Method in class smile.math.matrix.fp32.Matrix.SVD

Solves the least squares min || B - A*X ||.

solve(float[]) - Method in class smile.math.matrix.fp32.SymmMatrix.BunchKaufman

Solve A * x = b.

solve(float[]) - Method in class smile.math.matrix.fp32.SymmMatrix.Cholesky

Solves the linear system A * x = b.

solve(float[], float[]) - Method in class smile.math.matrix.fp32.IMatrix

Solves A * x = b by iterative biconjugate gradient method with Jacobi preconditioner matrix.

solve(float[], float[], IMatrix.Preconditioner, float, int, int) - Method in class smile.math.matrix.fp32.IMatrix

Solves A * x = b by iterative biconjugate gradient method.

solve(BigMatrix) - Method in class smile.math.matrix.BigMatrix.Cholesky

Solves the linear system A * X = B.

solve(BigMatrix) - Method in class smile.math.matrix.BigMatrix.LU

Solve A * X = B.

solve(BigMatrix) - Method in class smile.math.matrix.BigMatrix.QR

Solves the least squares min || B - A*X ||.

solve(Matrix) - Method in class smile.math.matrix.fp32.BandMatrix.Cholesky

Solves the linear system A * X = B.

solve(Matrix) - Method in class smile.math.matrix.fp32.BandMatrix.LU

Solve A * X = B.

solve(Matrix) - Method in class smile.math.matrix.fp32.Matrix.Cholesky

Solves the linear system A * X = B.

solve(Matrix) - Method in class smile.math.matrix.fp32.Matrix.LU

Solve A * X = B.

solve(Matrix) - Method in class smile.math.matrix.fp32.Matrix.QR

Solves the least squares min || B - A*X ||.

solve(Matrix) - Method in class smile.math.matrix.fp32.SymmMatrix.BunchKaufman

Solve A * X = B.

solve(Matrix) - Method in class smile.math.matrix.fp32.SymmMatrix.Cholesky

Solves the linear system A * X = B.

solve(Matrix) - Method in class smile.math.matrix.BandMatrix.Cholesky

Solves the linear system A * X = B.

solve(Matrix) - Method in class smile.math.matrix.BandMatrix.LU

Solve A * X = B.

solve(Matrix) - Method in class smile.math.matrix.Matrix.Cholesky

Solves the linear system A * X = B.

solve(Matrix) - Method in class smile.math.matrix.Matrix.LU

Solve A * X = B.

solve(Matrix) - Method in class smile.math.matrix.Matrix.QR

Solves the least squares min || B - A*X ||.

solve(Matrix) - Method in class smile.math.matrix.SymmMatrix.BunchKaufman

Solve A * X = B.

solve(Matrix) - Method in class smile.math.matrix.SymmMatrix.Cholesky

Solves the linear system A * X = B.

SOM - Class in smile.vq

Self-Organizing Map.

SOM(double[][][], TimeFunction, Neighborhood) - Constructor for class smile.vq.SOM

Constructor.

sort() - Method in class smile.math.matrix.BigMatrix.EVD

Sorts the eigenvalues in descending order and reorders the corresponding eigenvectors.

sort() - Method in class smile.math.matrix.fp32.Matrix.EVD

Sorts the eigenvalues in descending order and reorders the corresponding eigenvectors.

sort() - Method in class smile.math.matrix.Matrix.EVD

Sorts the eigenvalues in descending order and reorders the corresponding eigenvectors.

sort() - Method in class smile.sort.DoubleHeapSelect

Sort the smallest values.

sort() - Method in class smile.sort.FloatHeapSelect

Sort the smallest values.

sort() - Method in class smile.sort.HeapSelect

Sort the smallest values.

sort() - Method in class smile.sort.IntHeapSelect

Sort the smallest values.

sort() - Method in class smile.util.SparseArray

Sorts the array elements such that the indices are in ascending order.

sort(double[]) - Static method in interface smile.sort.HeapSort

Sorts the specified array into ascending numerical order.

sort(double[]) - Static method in class smile.sort.QuickSort

Sorts the specified array into ascending numerical order.

sort(double[]) - Static method in interface smile.sort.ShellSort

Sorts the specified array into ascending numerical order.

sort(double[][]) - Static method in class smile.math.MathEx

Sorts each variable and returns the index of values in ascending order.

sort(double[], double[]) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(double[], double[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(double[], int[]) - Static method in class smile.sort.QuickSort

Besides sorting the array x, the array y will be also rearranged as the same order of x.

sort(double[], int[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(double[], Object[]) - Static method in class smile.sort.QuickSort

Besides sorting the array x, the array y will be also rearranged as the same order of x.

sort(double[], Object[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(float[]) - Static method in interface smile.sort.HeapSort

Sorts the specified array into ascending numerical order.

sort(float[]) - Static method in class smile.sort.QuickSort

Sorts the specified array into ascending numerical order.

sort(float[]) - Static method in interface smile.sort.ShellSort

Sorts the specified array into ascending numerical order.

sort(float[], float[]) - Static method in class smile.sort.QuickSort

Besides sorting the array x, the array y will be also rearranged as the same order of x.

sort(float[], float[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(float[], int[]) - Static method in class smile.sort.QuickSort

Besides sorting the array x, the array y will be also rearranged as the same order of x.

sort(float[], int[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(float[], Object[]) - Static method in class smile.sort.QuickSort

Besides sorting the array x, the array y will be also rearranged as the same order of x.

sort(float[], Object[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(int[]) - Static method in interface smile.sort.HeapSort

Sorts the specified array into ascending numerical order.

sort(int[]) - Static method in class smile.sort.QuickSort

Sorts the specified array into ascending numerical order.

sort(int[]) - Static method in interface smile.sort.ShellSort

Sorts the specified array into ascending numerical order.

sort(int[], double[]) - Static method in class smile.sort.QuickSort

Besides sorting the array x, the array y will be also rearranged as the same order of x.

sort(int[], double[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(int[], int[]) - Static method in class smile.sort.QuickSort

Besides sorting the array x, the array y will be also rearranged as the same order of x.

sort(int[], int[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(int[], Object[]) - Static method in class smile.sort.QuickSort

Besides sorting the array x, the array y will be also rearranged as the same order of x.

sort(int[], Object[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(String) - Method in class smile.plot.vega.Field

Sets the sorting property.

sort(String...) - Method in class smile.plot.vega.StackTransform

Sets the fields for sorting data objects within a window.

sort(String...) - Method in class smile.plot.vega.WindowTransform

Sets the fields for sorting data objects within a window.

sort(SortField...) - Method in class smile.plot.vega.StackTransform

Sets the fields for sorting data objects within a window.

sort(SortField...) - Method in class smile.plot.vega.WindowTransform

Sets the fields for sorting data objects within a window.

sort(T[]) - Static method in interface smile.sort.HeapSort

Sorts the specified array into ascending order.

sort(T[]) - Static method in class smile.sort.QuickSort

Sorts the specified array into ascending order.

sort(T[]) - Static method in interface smile.sort.ShellSort

Sorts the specified array into ascending order.

sort(T[], int[]) - Static method in class smile.sort.QuickSort

Besides sorting the array x, the array y will be also rearranged as the same order of x.

sort(T[], int[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(T[], int[], int, Comparator<T>) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

sort(T[], Object[]) - Static method in class smile.sort.QuickSort

Besides sorting the array x, the array y will be also rearranged as the same order of x.

sort(T[], Object[], int) - Static method in class smile.sort.QuickSort

This is an efficient implementation Quick Sort algorithm without recursive.

Sort - Interface in smile.sort

Sort algorithm trait that includes useful static functions such as swap and swift up/down used in many sorting algorithms.

sortbfs() - Method in class smile.graph.AdjacencyList

sortbfs() - Method in class smile.graph.AdjacencyMatrix

sortbfs() - Method in interface smile.graph.Graph

Topological sort digraph by breadth-first search of graph.

sortdfs() - Method in class smile.graph.AdjacencyList

sortdfs() - Method in class smile.graph.AdjacencyMatrix

sortdfs() - Method in interface smile.graph.Graph

Reverse topological sort digraph by depth-first search of graph.

SortField - Record Class in smile.plot.vega

A sort field definition for sorting data objects within a window.

SortField(String, String) - Constructor for record class smile.plot.vega.SortField

Creates an instance of a SortField record class.

spacing(double) - Method in class smile.plot.vega.FacetField

Sets the spacing in pixels between facet's sub-views.

spacing(double) - Method in class smile.plot.vega.Field

For facet, row and column channels, sets the spacing in pixels between facet's sub-views.

spacing(int) - Method in class smile.plot.vega.Concat

spacing(int) - Method in class smile.plot.vega.Facet

spacing(int) - Method in class smile.plot.vega.FacetField

For the facet channel, sets the number of columns to include in the view composition layout.

spacing(int) - Method in class smile.plot.vega.Repeat

spacing(int) - Method in interface smile.plot.vega.ViewLayoutComposition

Sets the spacing in pixels between sub-views of the composition operator.

spacing(int, int) - Method in class smile.plot.vega.Concat

spacing(int, int) - Method in class smile.plot.vega.Facet

spacing(int, int) - Method in class smile.plot.vega.Repeat

spacing(int, int) - Method in interface smile.plot.vega.ViewLayoutComposition

Sets different spacing values for rows and columns.

sparse(int, int, String...) - Static method in class smile.feature.extraction.RandomProjection

Generates a sparse random projection.

sparse(int, KernelMachine<SparseArray>) - Static method in class smile.base.svm.LinearKernelMachine

Creates a linear kernel machine.

sparse(String) - Static method in interface smile.math.kernel.MercerKernel

Returns a sparse kernel function.

SparseArray - Class in smile.util

Sparse array of double values.

SparseArray() - Constructor for class smile.util.SparseArray

Constructor.

SparseArray(int) - Constructor for class smile.util.SparseArray

Constructor.

SparseArray(List<SparseArray.Entry>) - Constructor for class smile.util.SparseArray

Constructor.

SparseArray(Stream<SparseArray.Entry>) - Constructor for class smile.util.SparseArray

Constructor.

SparseArray.Entry - Class in smile.util

The entry in a sparse array of double values.

SparseBSC - Enum constant in enum class smile.deep.tensor.Layout

Sparse tensor in BSC format.

SparseBSR - Enum constant in enum class smile.deep.tensor.Layout

Sparse tensor in BSR format.

SparseChebyshevDistance - Class in smile.math.distance

Chebyshev distance (or Tchebychev distance), or L_∞ metric is a metric defined on a vector space where the distance between two vectors is the greatest of their differences along any coordinate dimension.

SparseChebyshevDistance() - Constructor for class smile.math.distance.SparseChebyshevDistance

Constructor.

SparseCOO - Enum constant in enum class smile.deep.tensor.Layout

Sparse tensor in COO format.

SparseCSC - Enum constant in enum class smile.deep.tensor.Layout

Sparse tensor in CSC format.

SparseCSR - Enum constant in enum class smile.deep.tensor.Layout

Sparse tensor in CSR format.

SparseDataset<T> - Interface in smile.data

List of Lists sparse matrix format.

SparseEncoder - Class in smile.feature.extraction

Encodes numeric and categorical features into sparse array with on-hot encoding of categorical variables.

SparseEncoder(StructType, String...) - Constructor for class smile.feature.extraction.SparseEncoder

Constructor.

SparseEuclideanDistance - Class in smile.math.distance

Euclidean distance on sparse arrays.

SparseEuclideanDistance() - Constructor for class smile.math.distance.SparseEuclideanDistance

Constructor.

SparseEuclideanDistance(double[]) - Constructor for class smile.math.distance.SparseEuclideanDistance

Constructor with a given weight vector.

SparseGaussianKernel - Class in smile.math.kernel

Gaussian kernel, also referred as RBF kernel or squared exponential kernel.

SparseGaussianKernel(double) - Constructor for class smile.math.kernel.SparseGaussianKernel

Constructor.

SparseGaussianKernel(double, double, double) - Constructor for class smile.math.kernel.SparseGaussianKernel

Constructor.

SparseHyperbolicTangentKernel - Class in smile.math.kernel

The hyperbolic tangent kernel on sparse data.

SparseHyperbolicTangentKernel() - Constructor for class smile.math.kernel.SparseHyperbolicTangentKernel

Constructor with scale 1.0 and offset 0.0.

SparseHyperbolicTangentKernel(double, double) - Constructor for class smile.math.kernel.SparseHyperbolicTangentKernel

Constructor.

SparseHyperbolicTangentKernel(double, double, double[], double[]) - Constructor for class smile.math.kernel.SparseHyperbolicTangentKernel

Constructor.

SparseLaplacianKernel - Class in smile.math.kernel

Laplacian kernel, also referred as exponential kernel.

SparseLaplacianKernel(double) - Constructor for class smile.math.kernel.SparseLaplacianKernel

Constructor.

SparseLaplacianKernel(double, double, double) - Constructor for class smile.math.kernel.SparseLaplacianKernel

Constructor.

SparseLinearKernel - Class in smile.math.kernel

The linear dot product kernel on sparse arrays.

SparseLinearKernel() - Constructor for class smile.math.kernel.SparseLinearKernel

Constructor.

SparseLogisticRegression - Class in smile.classification

Logistic regression on sparse data.

SparseLogisticRegression(int, double, double, IntSet) - Constructor for class smile.classification.SparseLogisticRegression

Constructor.

SparseLogisticRegression.Binomial - Class in smile.classification

Binomial logistic regression.

SparseLogisticRegression.Multinomial - Class in smile.classification

Multinomial logistic regression.

SparseManhattanDistance - Class in smile.math.distance

Manhattan distance, also known as L₁ distance or L₁ norm, is the sum of the (absolute) differences of their coordinates.

SparseManhattanDistance() - Constructor for class smile.math.distance.SparseManhattanDistance

Constructor.

SparseManhattanDistance(double[]) - Constructor for class smile.math.distance.SparseManhattanDistance

Constructor.

SparseMaternKernel - Class in smile.math.kernel

The class of Matérn kernels is a generalization of the Gaussian/RBF.

SparseMaternKernel(double, double) - Constructor for class smile.math.kernel.SparseMaternKernel

Constructor.

SparseMaternKernel(double, double, double, double) - Constructor for class smile.math.kernel.SparseMaternKernel

Constructor.

SparseMatrix - Class in smile.math.matrix.fp32

A sparse matrix is a matrix populated primarily with zeros.

SparseMatrix - Class in smile.math.matrix

A sparse matrix is a matrix populated primarily with zeros.

SparseMatrix(double[][]) - Constructor for class smile.math.matrix.SparseMatrix

Constructor.

SparseMatrix(double[][], double) - Constructor for class smile.math.matrix.SparseMatrix

Constructor.

SparseMatrix(float[][]) - Constructor for class smile.math.matrix.fp32.SparseMatrix

Constructor.

SparseMatrix(float[][], float) - Constructor for class smile.math.matrix.fp32.SparseMatrix

Constructor.

SparseMatrix(int, int, double[], int[], int[]) - Constructor for class smile.math.matrix.SparseMatrix

Constructor.

SparseMatrix(int, int, float[], int[], int[]) - Constructor for class smile.math.matrix.fp32.SparseMatrix

Constructor.

SparseMatrix.Entry - Class in smile.math.matrix.fp32

Encapsulates an entry in a matrix for use in streaming.

SparseMatrix.Entry - Class in smile.math.matrix

Encapsulates an entry in a matrix for use in streaming.

SparseMatrixPlot - Class in smile.plot.swing

A graphical representation of sparse matrix data.

SparseMatrixPlot(SparseMatrix, Color) - Constructor for class smile.plot.swing.SparseMatrixPlot

Constructor.

SparseMatrixPlot(SparseMatrix, Color[]) - Constructor for class smile.plot.swing.SparseMatrixPlot

Constructor.

SparseMinkowskiDistance - Class in smile.math.distance

Minkowski distance of order p or L_p-norm, is a generalization of Euclidean distance that is actually L₂-norm.

SparseMinkowskiDistance(int) - Constructor for class smile.math.distance.SparseMinkowskiDistance

Constructor.

SparseMinkowskiDistance(int, double[]) - Constructor for class smile.math.distance.SparseMinkowskiDistance

Constructor.

SparsePolynomialKernel - Class in smile.math.kernel

The polynomial kernel on sparse data.

SparsePolynomialKernel(int) - Constructor for class smile.math.kernel.SparsePolynomialKernel

Constructor with scale 1 and offset 0.

SparsePolynomialKernel(int, double, double) - Constructor for class smile.math.kernel.SparsePolynomialKernel

Constructor.

SparsePolynomialKernel(int, double, double, double[], double[]) - Constructor for class smile.math.kernel.SparsePolynomialKernel

Constructor.

SparseThinPlateSplineKernel - Class in smile.math.kernel

The Thin Plate Spline kernel on sparse data.

SparseThinPlateSplineKernel(double) - Constructor for class smile.math.kernel.SparseThinPlateSplineKernel

Constructor.

SparseThinPlateSplineKernel(double, double, double) - Constructor for class smile.math.kernel.SparseThinPlateSplineKernel

Constructor.

spearman(double[], double[]) - Static method in class smile.math.MathEx

The Spearman Rank Correlation Coefficient is a form of the Pearson coefficient with the data converted to rankings (ie.

spearman(double[], double[]) - Static method in class smile.stat.hypothesis.CorTest

Spearman rank correlation coefficient test.

spearman(float[], float[]) - Static method in class smile.math.MathEx

The Spearman Rank Correlation Coefficient is a form of the Pearson coefficient with the data converted to rankings (ie.

spearman(int[], int[]) - Static method in class smile.math.MathEx

The Spearman Rank Correlation Coefficient is a form of the Pearson coefficient with the data converted to rankings (ie.

spec() - Method in class smile.plot.vega.VegaLite

Returns the Vega-Lite specification.

spec() - Method in interface smile.plot.vega.ViewComposition

Returns the top level Vega-Lite specification.

specificity - Variable in class smile.validation.ClassificationMetrics

The specificity on validation data.

Specificity - Class in smile.validation.metric

Specificity (SPC) or True Negative Rate is a statistical measures of the performance of a binary classification test.

Specificity() - Constructor for class smile.validation.metric.Specificity

SpectralClustering - Class in smile.clustering

Spectral Clustering.

SpectralClustering(double, int, int[]) - Constructor for class smile.clustering.SpectralClustering

Constructor.

SphericalVariogram - Class in smile.interpolation.variogram

Spherical variogram.

SphericalVariogram(double, double) - Constructor for class smile.interpolation.variogram.SphericalVariogram

Constructor.

SphericalVariogram(double, double, double) - Constructor for class smile.interpolation.variogram.SphericalVariogram

Constructor.

split(String) - Method in class smile.nlp.tokenizer.BreakIteratorSentenceSplitter

split(String) - Method in class smile.nlp.tokenizer.BreakIteratorTokenizer

split(String) - Method in interface smile.nlp.tokenizer.ParagraphSplitter

Splits the text into paragraphs.

split(String) - Method in class smile.nlp.tokenizer.PennTreebankTokenizer

split(String) - Method in interface smile.nlp.tokenizer.SentenceSplitter

Splits the text into sentences.

split(String) - Method in class smile.nlp.tokenizer.SimpleParagraphSplitter

split(String) - Method in class smile.nlp.tokenizer.SimpleSentenceSplitter

split(String) - Method in class smile.nlp.tokenizer.SimpleTokenizer

split(String) - Method in interface smile.nlp.tokenizer.Tokenizer

Splits the string into a list of tokens.

split(Split, PriorityQueue<Split>) - Method in class smile.base.cart.CART

Split a node into two children nodes.

Split - Class in smile.base.cart

The data about of a potential split for a leaf node.

Split(LeafNode, int, double, int, int, int, int) - Constructor for class smile.base.cart.Split

Constructor.

SplitRule - Enum Class in smile.base.cart

The criterion to choose variable to split instances.

splom(DataFrame, char, Color) - Static method in class smile.plot.swing.PlotGrid

Scatterplot Matrix (SPLOM).

splom(DataFrame, char, String) - Static method in class smile.plot.swing.PlotGrid

Scatterplot Matrix (SPLOM).

spmv(Layout, UPLO, int, double, double[], double[], int, double, double[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric packed matrix.

spmv(Layout, UPLO, int, double, double[], double[], int, double, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

spmv(Layout, UPLO, int, double, DoubleBuffer, DoubleBuffer, int, double, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric packed matrix.

spmv(Layout, UPLO, int, double, DoubleBuffer, DoubleBuffer, int, double, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

spmv(Layout, UPLO, int, float, float[], float[], int, float, float[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric packed matrix.

spmv(Layout, UPLO, int, float, float[], float[], int, float, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

spmv(Layout, UPLO, int, float, FloatBuffer, FloatBuffer, int, float, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric packed matrix.

spmv(Layout, UPLO, int, float, FloatBuffer, FloatBuffer, int, float, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

spr(Layout, UPLO, int, double, double[], int, double[]) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation to symmetric packed matrix.

spr(Layout, UPLO, int, double, double[], int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS

spr(Layout, UPLO, int, double, DoubleBuffer, int, DoubleBuffer) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation to symmetric packed matrix.

spr(Layout, UPLO, int, double, DoubleBuffer, int, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

spr(Layout, UPLO, int, float, float[], int, float[]) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation to symmetric packed matrix.

spr(Layout, UPLO, int, float, float[], int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS

spr(Layout, UPLO, int, float, FloatBuffer, int, FloatBuffer) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation to symmetric packed matrix.

spr(Layout, UPLO, int, float, FloatBuffer, int, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

spsv(Layout, UPLO, int, int, double[], int[], double[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

spsv(Layout, UPLO, int, int, double[], int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

spsv(Layout, UPLO, int, int, float[], int[], float[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

spsv(Layout, UPLO, int, int, float[], int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

spsv(Layout, UPLO, int, int, DoubleBuffer, IntBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

spsv(Layout, UPLO, int, int, DoubleBuffer, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

spsv(Layout, UPLO, int, int, FloatBuffer, IntBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

spsv(Layout, UPLO, int, int, FloatBuffer, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

sptrf(Layout, UPLO, int, double[], int[]) - Method in interface smile.math.blas.LAPACK

Computes the Bunch–Kaufman factorization of a symmetric packed matrix A.

sptrf(Layout, UPLO, int, double[], int[]) - Method in class smile.math.blas.openblas.OpenBLAS

sptrf(Layout, UPLO, int, float[], int[]) - Method in interface smile.math.blas.LAPACK

Computes the Bunch–Kaufman factorization of a symmetric packed matrix A.

sptrf(Layout, UPLO, int, float[], int[]) - Method in class smile.math.blas.openblas.OpenBLAS

sptrf(Layout, UPLO, int, DoubleBuffer, IntBuffer) - Method in interface smile.math.blas.LAPACK

Computes the Bunch–Kaufman factorization of a symmetric packed matrix A.

sptrf(Layout, UPLO, int, DoubleBuffer, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

sptrf(Layout, UPLO, int, FloatBuffer, IntBuffer) - Method in interface smile.math.blas.LAPACK

Computes the Bunch–Kaufman factorization of a symmetric packed matrix A.

sptrf(Layout, UPLO, int, FloatBuffer, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

sptrs(Layout, UPLO, int, int, double[], int[], double[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

sptrs(Layout, UPLO, int, int, double[], int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

sptrs(Layout, UPLO, int, int, float[], int[], float[], int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

sptrs(Layout, UPLO, int, int, float[], int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

sptrs(Layout, UPLO, int, int, DoubleBuffer, IntBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

sptrs(Layout, UPLO, int, int, DoubleBuffer, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

sptrs(Layout, UPLO, int, int, FloatBuffer, IntBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a system of linear equations

sptrs(Layout, UPLO, int, int, FloatBuffer, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

SQL - Class in smile.data

An in-process SQL database management interface.

SQL() - Constructor for class smile.data.SQL

Constructor of in-memory database.

SQL(String) - Constructor for class smile.data.SQL

Constructor to open or create a persistent database.

sqrt(int[], int[]) - Static method in class smile.validation.metric.AdjustedMutualInformation

Calculates the adjusted mutual information of (I(y1, y2) - E(MI)) / (sqrt(H(y1) * H(y2)) - E(MI)).

sqrt(int[], int[]) - Static method in class smile.validation.metric.NormalizedMutualInformation

Calculates the normalized mutual information of I(y1, y2) / sqrt(H(y1) * H(y2)).

sqrt(String) - Static method in interface smile.data.formula.Terms

The sqrt(x) term.

sqrt(Term) - Static method in interface smile.data.formula.Terms

The sqrt(x) term.

SQRT - Enum constant in enum class smile.validation.metric.AdjustedMutualInformation.Method

I(y1, y2) / sqrt(H(y1) * H(y2))

SQRT - Enum constant in enum class smile.validation.metric.NormalizedMutualInformation.Method

I(y1, y2) / sqrt(H(y1) * H(y2))

SQRT - Static variable in class smile.validation.metric.AdjustedMutualInformation

Default instance with sqrt normalization.

SQRT - Static variable in class smile.validation.metric.NormalizedMutualInformation

Default instance with sqrt normalization.

square() - Method in class smile.math.matrix.fp32.IMatrix

Returns the square matrix of A' * A or A * A', whichever is smaller.

square() - Method in class smile.math.matrix.IMatrix

Returns the square matrix of A' * A or A * A', whichever is smaller.

squaredDistance(double[], double[]) - Static method in class smile.math.MathEx

The squared Euclidean distance.

squaredDistance(float[], float[]) - Static method in class smile.math.MathEx

The squared Euclidean distance.

squaredDistance(int[], int[]) - Static method in class smile.math.MathEx

The squared Euclidean distance on binary sparse arrays, which are the indices of nonzero elements in ascending order.

squaredDistance(SparseArray, SparseArray) - Static method in class smile.math.MathEx

The Euclidean distance on sparse arrays.

squaredDistanceWithMissingValues(double[], double[]) - Static method in class smile.math.MathEx

The squared Euclidean distance with handling missing values (represented as NaN).

SqueezeExcitation - Class in smile.vision.layer

Squeeze-and-Excitation block from "Squeeze-and-Excitation Networks".

SqueezeExcitation(int, int) - Constructor for class smile.vision.layer.SqueezeExcitation

Constructor.

SqueezeExcitation(int, int, ActivationFunction, ActivationFunction) - Constructor for class smile.vision.layer.SqueezeExcitation

Constructor.

SR - Enum constant in enum class smile.math.matrix.ARPACK.AsymmOption

The eigenvalues of smallest real part.

SR - Enum constant in enum class smile.math.matrix.fp32.ARPACK.AsymmOption

The eigenvalues of smallest real part.

sse - Variable in class smile.math.LevenbergMarquardt

The sum of squares due to error.

ssr - Variable in class smile.feature.selection.SumSquaresRatio

Sum squares ratio.

stack(String) - Method in class smile.plot.vega.Field

Sets the type of stacking offset if the field should be stacked.

stack(String, String, String...) - Method in class smile.plot.vega.Transform

Adds a stack transform.

StackTransform - Class in smile.plot.vega

The stack transform.

Staircase - Class in smile.plot.swing

This class represents a poly line in the plot.

Staircase(double[][], Color) - Constructor for class smile.plot.swing.Staircase

Constructor.

StaircasePlot - Class in smile.plot.swing

Staircase plot is a special case of line which is most useful to display empirical distribution.

StaircasePlot(Staircase...) - Constructor for class smile.plot.swing.StaircasePlot

Constructor.

StaircasePlot(Staircase[], Legend[]) - Constructor for class smile.plot.swing.StaircasePlot

Constructor.

standardize() - Method in class smile.math.matrix.BigMatrix

Standardizes the columns of matrix.

standardize() - Method in class smile.math.matrix.fp32.Matrix

Standardizes the columns of matrix.

standardize() - Method in class smile.math.matrix.Matrix

Standardizes the columns of matrix.

standardize(double[]) - Static method in class smile.math.MathEx

Standardizes an array to mean 0 and variance 1.

standardize(double[][]) - Static method in class smile.math.MathEx

Standardizes each column of a matrix to 0 mean and unit variance.

standardizer(double[]) - Static method in class smile.math.Scaler

Returns the standardize scaler to 0 mean and unit variance.

standardizer(double[], boolean) - Static method in class smile.math.Scaler

Returns the standardize scaler to 0 mean and unit variance.

Standardizer - Class in smile.feature.transform

Standardizes numeric feature to 0 mean and unit variance.

Standardizer() - Constructor for class smile.feature.transform.Standardizer

stateChanged(ChangeEvent) - Method in class smile.swing.Table.RowHeader

STEEL_BLUE - Static variable in interface smile.plot.swing.Palette

stem(String) - Method in class smile.nlp.stemmer.LancasterStemmer

stem(String) - Method in class smile.nlp.stemmer.PorterStemmer

stem(String) - Method in interface smile.nlp.stemmer.Stemmer

Transforms a word into its root form.

Stemmer - Interface in smile.nlp.stemmer

A Stemmer transforms a word into its root form.

step() - Method in class smile.deep.Optimizer

Updates the parameters based on the calculated gradients.

step(double) - Method in class smile.plot.vega.BinParams

Sets the exact step size between bins.

step(double) - Method in class smile.plot.vega.QuantileTransform

Sets a probability step size (default 0.01) for sampling quantile values.

step(int) - Method in class smile.plot.vega.ViewConfig

Sets the default step size for x-/y- discrete fields.

steps(double...) - Method in class smile.plot.vega.BinParams

Sets an array of allowable step sizes to choose from.

steps(int) - Method in class smile.plot.vega.DensityTransform

Sets the exact number of samples to take along the extent domain for plotting the density.

StochasticDepth - Class in smile.vision.layer

Stochastic Depth for randomly dropping residual branches of residual architectures, from "Deep Networks with Stochastic Depth".

StochasticDepth(double, String) - Constructor for class smile.vision.layer.StochasticDepth

Constructor.

stopCellEditing() - Method in class smile.swing.table.DateCellEditor

stopCellEditing() - Method in class smile.swing.table.DoubleArrayCellEditor

stopCellEditing() - Method in class smile.swing.table.DoubleCellEditor

stopCellEditing() - Method in class smile.swing.table.IntegerArrayCellEditor

stopCellEditing() - Method in class smile.swing.table.IntegerCellEditor

StopWords - Interface in smile.nlp.dictionary

A set of stop words in some language.

strata(int[]) - Static method in interface smile.stat.Sampling

Returns the strata of samples as a two-dimensional array.

stratify(int[], double) - Static method in interface smile.stat.Sampling

Stratified sampling from a population which can be partitioned into subpopulations.

stratify(int[], int) - Static method in interface smile.validation.CrossValidation

Cross validation with stratified folds.

stratify(int, int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.CrossValidation

Repeated stratified cross validation of classification.

stratify(int, int, T[], int[], BiFunction<T[], int[], M>) - Static method in interface smile.validation.CrossValidation

Repeated stratified cross validation of classification.

stratify(int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.CrossValidation

Stratified cross validation of classification.

stratify(int, T[], int[], BiFunction<T[], int[], M>) - Static method in interface smile.validation.CrossValidation

Stratified cross validation of classification.

stream() - Method in interface smile.data.DataFrame

Returns a (possibly parallel) Stream of rows.

stream() - Method in interface smile.data.Dataset

Returns a (possibly parallel) Stream with this collection as its source.

stream() - Method in class smile.data.IndexDataFrame

stream() - Method in interface smile.data.vector.BaseVector

Returns a stream of vector elements.

stream() - Method in class smile.util.DoubleArrayList

Returns the stream of the array list.

stream() - Method in class smile.util.IntArrayList

Returns the stream of the array list.

stream() - Method in class smile.util.SparseArray

Returns the stream of nonzero entries.

stream(String) - Static method in interface smile.io.HadoopInput

Returns the reader of a file path or URI.

stream(String) - Static method in interface smile.io.Input

Returns the input stream of a file path or URI.

stress - Variable in class smile.manifold.IsotonicMDS

The final stress achieved.

stress - Variable in class smile.manifold.SammonMapping

The final stress achieved.

stride() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns the value of the stride record component.

stride() - Method in record class smile.vision.layer.MBConvConfig

Returns the value of the stride record component.

Strided - Enum constant in enum class smile.deep.tensor.Layout

Dense tensor.

String - Enum constant in enum class smile.data.type.DataType.ID

String type ID.

Strings - Interface in smile.util

String utility functions.

StringType - Class in smile.data.type

String data type.

StringType - Static variable in class smile.data.type.DataTypes

String data type.

stringVector(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

stringVector(int) - Method in class smile.data.IndexDataFrame

stringVector(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

stringVector(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

StringVector - Interface in smile.data.vector

An immutable string vector.

stripPluralParticiple(String) - Method in class smile.nlp.stemmer.PorterStemmer

Removes plurals and participles.

stroke(String) - Method in class smile.plot.vega.Background

Sets the stroke color.

stroke(String) - Method in class smile.plot.vega.Mark

Sets the default stroke color.

stroke(String) - Method in class smile.plot.vega.ViewConfig

Sets the stroke color.

strokeCap(String) - Method in class smile.plot.vega.Background

Sets the stroke cap for line ending style.

strokeCap(String) - Method in class smile.plot.vega.Mark

Sets the stroke cap for line ending style.

strokeCap(String) - Method in class smile.plot.vega.ViewConfig

Sets the stroke cap for line ending style.

strokeColor(String) - Method in class smile.plot.vega.Legend

Sets the border stroke color for the full legend.

strokeDash(double, double) - Method in class smile.plot.vega.Background

Sets the alternating [stroke, space] lengths for stroke dash.

strokeDash(double, double) - Method in class smile.plot.vega.Mark

Sets the alternating [stroke, space] lengths for dashed lines.

strokeDash(double, double) - Method in class smile.plot.vega.ViewConfig

Sets the alternating [stroke, space] lengths for stroke dash.

strokeDashOffset(double) - Method in class smile.plot.vega.Mark

Sets the pixel offset at which to start drawing with the dash array.

strokeDashOffset(int) - Method in class smile.plot.vega.Background

Sets the offset (in pixels) into which to begin drawing with the stroke dash array.

strokeDashOffset(int) - Method in class smile.plot.vega.ViewConfig

Sets the offset (in pixels) into which to begin drawing with the stroke dash array.

strokeJoin(String) - Method in class smile.plot.vega.Background

Sets the stroke line join method.

strokeJoin(String) - Method in class smile.plot.vega.Mark

Sets the stroke line join method.

strokeJoin(String) - Method in class smile.plot.vega.ViewConfig

Sets the stroke line join method.

strokeMiterLimit(double) - Method in class smile.plot.vega.Mark

Sets the miter limit at which to bevel a line join.

strokeMiterLimit(int) - Method in class smile.plot.vega.Background

Sets the miter limit at which to bevel a line join.

strokeMiterLimit(int) - Method in class smile.plot.vega.ViewConfig

Sets the miter limit at which to bevel a line join.

strokeOpacity(double) - Method in class smile.plot.vega.Background

Sets the stroke opacity

strokeOpacity(double) - Method in class smile.plot.vega.Mark

Sets the stroke opacity.

strokeOpacity(double) - Method in class smile.plot.vega.ViewConfig

Sets the stroke opacity

strokeWidth(double) - Method in class smile.plot.vega.Mark

Sets the stroke width of axis domain line.

strokeWidth(int) - Method in class smile.plot.vega.Background

Sets the stroke width.

strokeWidth(int) - Method in class smile.plot.vega.ViewConfig

Sets the stroke width.

struct(ResultSet) - Static method in class smile.data.type.DataTypes

Creates a struct data type from JDBC result set meta data.

struct(ResultSetMetaData, String) - Static method in class smile.data.type.DataTypes

Creates a struct data type from JDBC result set meta data.

struct(List<StructField>) - Static method in class smile.data.type.DataTypes

Creates a struct data type.

struct(StructField...) - Static method in class smile.data.type.DataTypes

Creates a struct data type.

Struct - Enum constant in enum class smile.data.type.DataType.ID

Struct type ID.

StructField - Class in smile.data.type

A field in a Struct data type.

StructField(String, DataType) - Constructor for class smile.data.type.StructField

Constructor.

StructField(String, DataType, Measure) - Constructor for class smile.data.type.StructField

Constructor.

StructType - Class in smile.data.type

Struct data type is determined by the fixed order of the fields of primitive data types in the struct.

StructType(List<StructField>) - Constructor for class smile.data.type.StructType

Constructor.

StructType(StructField...) - Constructor for class smile.data.type.StructType

Constructor.

structure() - Method in interface smile.data.DataFrame

Returns the structure of data frame.

sturges(int) - Static method in interface smile.math.Histogram

Returns the number of bins by Sturges' rule k = ceil(log2(n) + 1).

style(String...) - Method in class smile.plot.vega.Axis

Sets the custom styles to apply to the axis.

style(String...) - Method in class smile.plot.vega.Background

Sets the custom styles.

style(String...) - Method in class smile.plot.vega.Mark

Sets the style.

sub(double) - Method in class smile.deep.tensor.Tensor

Returns A -= b.

sub(double) - Method in class smile.math.matrix.BigMatrix

A -= b

sub(double) - Method in class smile.math.matrix.Matrix

A -= b

sub(double) - Method in class smile.util.Array2D

A -= x.

sub(double[], double[]) - Static method in class smile.math.MathEx

Element-wise subtraction of two arrays y = y - x.

sub(float) - Method in class smile.deep.tensor.Tensor

Returns A - b.

sub(float) - Method in class smile.math.matrix.fp32.Matrix

A -= b

sub(int) - Method in class smile.util.IntArray2D

A -= x.

sub(int, int, double) - Method in class smile.math.matrix.BigMatrix

A[i,j] -= b

sub(int, int, double) - Method in class smile.math.matrix.Matrix

A[i,j] -= b

sub(int, int, double) - Method in class smile.util.Array2D

A[i, j] -= x.

sub(int, int, float) - Method in class smile.math.matrix.fp32.Matrix

A[i,j] -= b

sub(int, int, int) - Method in class smile.util.IntArray2D

A[i, j] -= x.

sub(String, String) - Static method in interface smile.data.formula.Terms

Subtracts two terms.

sub(String, Term) - Static method in interface smile.data.formula.Terms

Subtracts two terms.

sub(Term, String) - Static method in interface smile.data.formula.Terms

Subtracts two terms.

sub(Term, Term) - Static method in interface smile.data.formula.Terms

Subtracts two terms.

sub(Tensor) - Method in class smile.deep.tensor.Tensor

Returns A - B.

sub(Tensor, double) - Method in class smile.deep.tensor.Tensor

Returns A - alpha * B.

sub(Complex) - Method in class smile.math.Complex

Returns this - b.

sub(BigMatrix) - Method in class smile.math.matrix.BigMatrix

Element-wise subtraction A -= B

sub(Matrix) - Method in class smile.math.matrix.fp32.Matrix

Element-wise subtraction A -= B

sub(Matrix) - Method in class smile.math.matrix.Matrix

Element-wise subtraction A -= B

sub(Array2D) - Method in class smile.util.Array2D

A -= B.

sub(IntArray2D) - Method in class smile.util.IntArray2D

A -= B.

Sub - Class in smile.data.formula

The term of a - b expression.

Sub(Term, Term) - Constructor for class smile.data.formula.Sub

Constructor.

sub_(double) - Method in class smile.deep.tensor.Tensor

Returns A -= b.

sub_(float) - Method in class smile.deep.tensor.Tensor

Returns A - b.

sub_(Tensor) - Method in class smile.deep.tensor.Tensor

Returns A -= B.

sub_(Tensor, double) - Method in class smile.deep.tensor.Tensor

Returns A -= alpha * B.

subgraph(int[]) - Method in class smile.graph.AdjacencyList

subgraph(int[]) - Method in class smile.graph.AdjacencyMatrix

subgraph(int[]) - Method in interface smile.graph.Graph

Returns a subgraph containing all given vertices.

submatrix(int, int, int, int) - Method in class smile.math.matrix.BigMatrix

Returns the submatrix which top left at (i, j) and bottom right at (k, l).

submatrix(int, int, int, int) - Method in class smile.math.matrix.fp32.Matrix

Returns the submatrix which top left at (i, j) and bottom right at (k, l).

submatrix(int, int, int, int) - Method in class smile.math.matrix.Matrix

Returns the submatrix which top left at (i, j) and bottom right at (k, l).

sum() - Method in class smile.deep.tensor.Tensor

Returns the sum of all elements in the tensor.

sum() - Method in class smile.math.matrix.BigMatrix

Returns the sum of all elements.

sum() - Method in class smile.math.matrix.fp32.Matrix

Returns the sum of all elements.

sum() - Method in class smile.math.matrix.Matrix

Returns the sum of all elements.

sum() - Method in class smile.util.Array2D

Returns the sum of all elements.

sum() - Method in class smile.util.IntArray2D

Returns the sum of all elements.

sum(byte[]) - Static method in class smile.math.MathEx

Returns the sum of an array.

sum(double[]) - Static method in class smile.math.MathEx

Returns the sum of an array.

sum(float[]) - Static method in class smile.math.MathEx

Returns the sum of an array.

sum(int[]) - Static method in class smile.math.MathEx

Returns the sum of an array.

sum(int[], int[]) - Static method in class smile.validation.metric.AdjustedMutualInformation

Calculates the adjusted mutual information of (I(y1, y2) - E(MI)) / (0.5 * (H(y1) + H(y2)) - E(MI)).

sum(int[], int[]) - Static method in class smile.validation.metric.NormalizedMutualInformation

Calculates the normalized mutual information of 2 * I(y1, y2) / (H(y1) + H(y2)).

SUM - Enum constant in enum class smile.validation.metric.AdjustedMutualInformation.Method

2 * I(y1, y2) / (H(y1) + H(y2))

SUM - Enum constant in enum class smile.validation.metric.NormalizedMutualInformation.Method

2 * I(y1, y2) / (H(y1) + H(y2))

SUM - Static variable in class smile.validation.metric.AdjustedMutualInformation

Default instance with sum normalization.

SUM - Static variable in class smile.validation.metric.NormalizedMutualInformation

Default instance with sum normalization.

SumKernel<T> - Class in smile.math.kernel

The sum kernel takes two kernels and combines them via k1(x, y) + k2(x, y)

SumKernel(MercerKernel<T>, MercerKernel<T>) - Constructor for class smile.math.kernel.SumKernel

Constructor.

summary() - Method in interface smile.data.DataFrame

Returns the statistic summary of numeric columns.

SumSquaresRatio - Class in smile.feature.selection

The ratio of between-groups to within-groups sum of squares is a univariate feature ranking metric, which can be used as a feature selection criterion for multi-class classification problems.

SumSquaresRatio(String, double) - Constructor for class smile.feature.selection.SumSquaresRatio

Constructor.

support - Variable in class smile.association.AssociationRule

The support value.

support - Variable in class smile.association.ItemSet

The associated support of item set.

SupportVector<T> - Class in smile.base.svm

Support vector.

SupportVector(int, T, int, double, double, double, double, double) - Constructor for class smile.base.svm.SupportVector

Constructor.

Surface - Class in smile.plot.swing

A surface object gives 3D information e.g.

Surface(double[][][]) - Constructor for class smile.plot.swing.Surface

Constructor for irregular mesh grid.

Surface(double[][][], Color[]) - Constructor for class smile.plot.swing.Surface

Constructor for irregular mesh surface.

svd() - Method in class smile.math.matrix.BigMatrix

Singular Value Decomposition.

svd() - Method in class smile.math.matrix.fp32.Matrix

Singular Value Decomposition.

svd() - Method in class smile.math.matrix.Matrix

Singular Value Decomposition.

svd(boolean, boolean) - Method in class smile.math.matrix.BigMatrix

Singular Value Decomposition.

svd(boolean, boolean) - Method in class smile.math.matrix.fp32.Matrix

Singular Value Decomposition.

svd(boolean, boolean) - Method in class smile.math.matrix.Matrix

Singular Value Decomposition.

svd(IMatrix, int) - Static method in class smile.math.matrix.fp32.ARPACK

Computes k largest approximate singular triples of a matrix.

svd(IMatrix, int, int, float) - Static method in class smile.math.matrix.fp32.ARPACK

Computes k largest approximate singular triples of a matrix.

svd(IMatrix, int) - Static method in class smile.math.matrix.ARPACK

Computes k largest approximate singular triples of a matrix.

svd(IMatrix, int, int, double) - Static method in class smile.math.matrix.ARPACK

Computes k largest approximate singular triples of a matrix.

SVD(double[], Matrix, Matrix) - Constructor for class smile.math.matrix.Matrix.SVD

Constructor.

SVD(float[], Matrix, Matrix) - Constructor for class smile.math.matrix.fp32.Matrix.SVD

Constructor.

SVD(int, int, double[]) - Constructor for class smile.math.matrix.Matrix.SVD

Constructor.

SVD(int, int, float[]) - Constructor for class smile.math.matrix.fp32.Matrix.SVD

Constructor.

SVD(int, int, DoublePointer) - Constructor for class smile.math.matrix.BigMatrix.SVD

Constructor.

SVD(DoublePointer, BigMatrix, BigMatrix) - Constructor for class smile.math.matrix.BigMatrix.SVD

Constructor.

SVDImputer - Interface in smile.feature.imputation

Missing value imputation with singular value decomposition.

SVDJob - Enum Class in smile.math.blas

The option if computing singular vectors.

SVM<T> - Class in smile.anomaly

One-class support vector machines for novelty detection.

SVM<T> - Class in smile.classification

Support vector machines for classification.

SVM - Class in smile.regression

Epsilon support vector regression.

SVM() - Constructor for class smile.regression.SVM

SVM(MercerKernel<T>, T[], double[], double) - Constructor for class smile.anomaly.SVM

Constructor.

SVM(MercerKernel<T>, T[], double[], double) - Constructor for class smile.classification.SVM

Constructor.

SVR<T> - Class in smile.base.svm

Epsilon support vector regression.

SVR(MercerKernel<T>, double, double, double) - Constructor for class smile.base.svm.SVR

Constructor.

swap(double[], double[]) - Method in interface smile.math.blas.BLAS

Swaps two vectors.

swap(double[], double[]) - Static method in class smile.math.MathEx

Swap two arrays.

swap(double[], int, int) - Static method in class smile.math.MathEx

Swap two elements of an array.

swap(double[], int, int) - Static method in interface smile.sort.Sort

Swap two positions.

swap(float[], float[]) - Method in interface smile.math.blas.BLAS

Swaps two vectors.

swap(float[], float[]) - Static method in class smile.math.MathEx

Swap two arrays.

swap(float[], int, int) - Static method in class smile.math.MathEx

Swap two elements of an array.

swap(float[], int, int) - Static method in interface smile.sort.Sort

Swap two positions.

swap(int[], int[]) - Static method in class smile.math.MathEx

Swap two arrays.

swap(int[], int, int) - Static method in class smile.math.MathEx

Swap two elements of an array.

swap(int[], int, int) - Static method in interface smile.sort.Sort

Swap two positions.

swap(int, double[], int, double[], int) - Method in interface smile.math.blas.BLAS

Swaps two vectors.

swap(int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

swap(int, float[], int, float[], int) - Method in interface smile.math.blas.BLAS

Swaps two vectors.

swap(int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

swap(E[], E[]) - Static method in class smile.math.MathEx

Swap two arrays.

swap(Object[], int, int) - Static method in class smile.math.MathEx

Swap two elements of an array.

swap(Object[], int, int) - Static method in interface smile.sort.Sort

Swap two positions.

syev(Layout, EVDJob, UPLO, int, double[], int, double[]) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syev(Layout, EVDJob, UPLO, int, double[], int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS

syev(Layout, EVDJob, UPLO, int, float[], int, float[]) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syev(Layout, EVDJob, UPLO, int, float[], int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS

syev(Layout, EVDJob, UPLO, int, DoubleBuffer, int, DoubleBuffer) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syev(Layout, EVDJob, UPLO, int, DoubleBuffer, int, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

syev(Layout, EVDJob, UPLO, int, FloatBuffer, int, FloatBuffer) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syev(Layout, EVDJob, UPLO, int, FloatBuffer, int, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

syev(IMatrix, ARPACK.SymmOption, int) - Static method in class smile.math.matrix.fp32.ARPACK

Computes NEV eigenvalues of a symmetric single precision matrix.

syev(IMatrix, ARPACK.SymmOption, int, int, float) - Static method in class smile.math.matrix.fp32.ARPACK

Computes NEV eigenvalues of a symmetric single precision matrix.

syev(IMatrix, ARPACK.SymmOption, int) - Static method in class smile.math.matrix.ARPACK

Computes NEV eigenvalues of a symmetric double precision matrix.

syev(IMatrix, ARPACK.SymmOption, int, int, double) - Static method in class smile.math.matrix.ARPACK

Computes NEV eigenvalues of a symmetric double precision matrix.

syevd(Layout, EVDJob, UPLO, int, double[], int, double[]) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syevd(Layout, EVDJob, UPLO, int, double[], int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS

syevd(Layout, EVDJob, UPLO, int, float[], int, float[]) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syevd(Layout, EVDJob, UPLO, int, float[], int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS

syevd(Layout, EVDJob, UPLO, int, DoubleBuffer, int, DoubleBuffer) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syevd(Layout, EVDJob, UPLO, int, DoubleBuffer, int, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

syevd(Layout, EVDJob, UPLO, int, FloatBuffer, int, FloatBuffer) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syevd(Layout, EVDJob, UPLO, int, FloatBuffer, int, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

syevd(Layout, EVDJob, UPLO, int, DoublePointer, int, DoublePointer) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syevd(Layout, EVDJob, UPLO, int, DoublePointer, int, DoublePointer) - Method in class smile.math.blas.openblas.OpenBLAS

syevr(Layout, EVDJob, EigenRange, UPLO, int, double[], int, double, double, int, int, double, int[], double[], double[], int, int[]) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syevr(Layout, EVDJob, EigenRange, UPLO, int, double[], int, double, double, int, int, double, int[], double[], double[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

syevr(Layout, EVDJob, EigenRange, UPLO, int, float[], int, float, float, int, int, float, int[], float[], float[], int, int[]) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syevr(Layout, EVDJob, EigenRange, UPLO, int, float[], int, float, float, int, int, float, int[], float[], float[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS

syevr(Layout, EVDJob, EigenRange, UPLO, int, DoubleBuffer, int, double, double, int, int, double, IntBuffer, DoubleBuffer, DoubleBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syevr(Layout, EVDJob, EigenRange, UPLO, int, DoubleBuffer, int, double, double, int, int, double, IntBuffer, DoubleBuffer, DoubleBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

syevr(Layout, EVDJob, EigenRange, UPLO, int, FloatBuffer, int, float, float, int, int, float, IntBuffer, FloatBuffer, FloatBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK

Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a real symmetric matrix A.

syevr(Layout, EVDJob, EigenRange, UPLO, int, FloatBuffer, int, float, float, int, int, float, IntBuffer, FloatBuffer, FloatBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS

SYM - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Symbol.

symbolLimit(int) - Method in class smile.plot.vega.Legend

Sets the maximum number of allowed entries for a symbol legend.

SymletWavelet - Class in smile.wavelet

Symlet wavelets.

SymletWavelet(int) - Constructor for class smile.wavelet.SymletWavelet

Constructor.

symm(Layout, Side, UPLO, int, int, double, double[], int, double[], int, double, double[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-matrix operation where the matrix A is symmetric.

symm(Layout, Side, UPLO, int, int, double, double[], int, double[], int, double, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

symm(Layout, Side, UPLO, int, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-matrix operation where the matrix A is symmetric.

symm(Layout, Side, UPLO, int, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

symm(Layout, Side, UPLO, int, int, double, DoublePointer, int, DoublePointer, int, double, DoublePointer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-matrix operation where the matrix A is symmetric.

symm(Layout, Side, UPLO, int, int, double, DoublePointer, int, DoublePointer, int, double, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

symm(Layout, Side, UPLO, int, int, float, float[], int, float[], int, float, float[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-matrix operation where one input matrix is symmetric.

symm(Layout, Side, UPLO, int, int, float, float[], int, float[], int, float, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

symm(Layout, Side, UPLO, int, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-matrix operation where one input matrix is symmetric.

symm(Layout, Side, UPLO, int, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

SymmMatrix - Class in smile.math.matrix.fp32

The symmetric matrix in packed storage.

SymmMatrix - Class in smile.math.matrix

The symmetric matrix in packed storage.

SymmMatrix(UPLO, double[][]) - Constructor for class smile.math.matrix.SymmMatrix

Constructor.

SymmMatrix(UPLO, float[][]) - Constructor for class smile.math.matrix.fp32.SymmMatrix

Constructor.

SymmMatrix(UPLO, int) - Constructor for class smile.math.matrix.fp32.SymmMatrix

Constructor.

SymmMatrix(UPLO, int) - Constructor for class smile.math.matrix.SymmMatrix

Constructor.

SymmMatrix.BunchKaufman - Class in smile.math.matrix.fp32

The LU decomposition.

SymmMatrix.BunchKaufman - Class in smile.math.matrix

The LU decomposition.

SymmMatrix.Cholesky - Class in smile.math.matrix.fp32

The Cholesky decomposition of a symmetric, positive-definite matrix.

SymmMatrix.Cholesky - Class in smile.math.matrix

The Cholesky decomposition of a symmetric, positive-definite matrix.

symv(Layout, UPLO, int, double, double[], int, double[], int, double, double[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric matrix.

symv(Layout, UPLO, int, double, double[], int, double[], int, double, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

symv(Layout, UPLO, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric matrix.

symv(Layout, UPLO, int, double, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

symv(Layout, UPLO, int, double, DoublePointer, int, DoublePointer, int, double, DoublePointer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric matrix.

symv(Layout, UPLO, int, double, DoublePointer, int, DoublePointer, int, double, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

symv(Layout, UPLO, int, float, float[], int, float[], int, float, float[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric matrix.

symv(Layout, UPLO, int, float, float[], int, float[], int, float, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

symv(Layout, UPLO, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a symmetric matrix.

symv(Layout, UPLO, int, float, FloatBuffer, int, FloatBuffer, int, float, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

syr(Layout, UPLO, int, double, double[], int, double[], int) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation to symmetric matrix.

syr(Layout, UPLO, int, double, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

syr(Layout, UPLO, int, double, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation to symmetric matrix.

syr(Layout, UPLO, int, double, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

syr(Layout, UPLO, int, double, DoublePointer, int, DoublePointer, int) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation to symmetric matrix.

syr(Layout, UPLO, int, double, DoublePointer, int, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

syr(Layout, UPLO, int, float, float[], int, float[], int) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation to symmetric matrix.

syr(Layout, UPLO, int, float, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

syr(Layout, UPLO, int, float, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the rank-1 update operation to symmetric matrix.

syr(Layout, UPLO, int, float, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

sysv(Layout, UPLO, int, int, double[], int, int[], double[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

sysv(Layout, UPLO, int, int, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

sysv(Layout, UPLO, int, int, float[], int, int[], float[], int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

sysv(Layout, UPLO, int, int, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

sysv(Layout, UPLO, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

sysv(Layout, UPLO, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

sysv(Layout, UPLO, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

sysv(Layout, UPLO, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

sysv(Layout, UPLO, int, int, DoublePointer, int, IntPointer, DoublePointer, int) - Method in interface smile.math.blas.LAPACK

Solves a real system of linear equations.

sysv(Layout, UPLO, int, int, DoublePointer, int, IntPointer, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

T

t - Variable in class smile.base.mlp.MultilayerPerceptron

The training iterations.

t - Variable in class smile.feature.extraction.GHA

The training iterations.

t - Variable in class smile.stat.hypothesis.CorTest

The test statistic.

t - Variable in class smile.stat.hypothesis.TTest

t-statistic.

T - Variable in class smile.vq.BIRCH

THe maximum radius of a sub-cluster.

table - Variable in class smile.validation.metric.ContingencyTable

The contingency table.

Table - Class in smile.swing

Customized JTable with optional row number header.

Table() - Constructor for class smile.swing.Table

Constructs a default JTable that is initialized with a default data model, a default column model, and a default selection model.

Table(int, int) - Constructor for class smile.swing.Table

Constructs a JTable with numRows and numColumns of empty cells using DefaultTableModel.

Table(Object[][], Object[]) - Constructor for class smile.swing.Table

Constructs a JTable to display the values in the two dimensional array, rowData, with column names, columnNames.

Table(TableModel) - Constructor for class smile.swing.Table

Constructs a JTable that is initialized with dm as the data model, a default column model, and a default selection model.

Table(TableModel, TableColumnModel) - Constructor for class smile.swing.Table

Constructs a JTable that is initialized with dm as the data model, cm as the column model, and a default selection model.

Table(TableModel, TableColumnModel, ListSelectionModel) - Constructor for class smile.swing.Table

Constructs a JTable that is initialized with dm as the data model, cm as the column model, and sm as the selection model

Table.RowHeader - Class in smile.swing

Use a JTable as a renderer for row numbers of the main table.

TableColumnSettings - Class in smile.swing.table

Table column settings.

TableColumnSettings(String) - Constructor for class smile.swing.table.TableColumnSettings

Constructor.

TableCopyPasteAdapter - Class in smile.swing.table

TableCopyPasteAdapter enables Copy-Paste Clipboard functionality on JTables.

tables() - Method in class smile.data.SQL

Returns the tables in the database.

tag(String[]) - Method in class smile.nlp.pos.HMMPOSTagger

tag(String[]) - Method in interface smile.nlp.pos.POSTagger

Tags the sentence in the form of a sequence of words.

tan() - Method in class smile.math.Complex

Returns the complex tangent.

tan(String) - Static method in interface smile.data.formula.Terms

The tan(x) term.

tan(Term) - Static method in interface smile.data.formula.Terms

The tan(x) term.

tanh() - Static method in interface smile.base.mlp.activation.ActivationFunction

Returns the hyperbolic tangent activation function.

tanh() - Static method in interface smile.base.mlp.ActivationFunction

Hyperbolic tangent activation function.

tanh(int) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with hyperbolic tangent activation function.

tanh(int, double) - Static method in class smile.base.mlp.Layer

Returns a hidden layer with hyperbolic tangent activation function.

tanh(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with tanh activation function.

tanh(String) - Static method in interface smile.data.formula.Terms

The tanh(x) term.

tanh(Term) - Static method in interface smile.data.formula.Terms

The tanh(x) term.

Tanh - Class in smile.base.mlp.activation

Hyperbolic tangent activation function.

Tanh - Class in smile.deep.activation

Hyperbolic Tangent activation function.

Tanh() - Constructor for class smile.base.mlp.activation.Tanh

Constructor.

Tanh(boolean) - Constructor for class smile.deep.activation.Tanh

Constructor.

tanhShrink(int, int) - Static method in interface smile.deep.layer.Layer

Returns a fully connected layer with tanh shrink activation function.

TanhShrink - Class in smile.deep.activation

Hyperbolic Tangent Shrink activation function.

TanhShrink() - Constructor for class smile.deep.activation.TanhShrink

Constructor.

target - Variable in class smile.base.mlp.MultilayerPerceptron

The buffer to store desired target value of training instance.

target() - Method in record class smile.deep.SampleBatch

Returns the value of the target record component.

tau - Variable in class smile.math.matrix.BigMatrix.QR

The scalar factors of the elementary reflectors

tau - Variable in class smile.math.matrix.fp32.Matrix.QR

The scalar factors of the elementary reflectors

tau - Variable in class smile.math.matrix.Matrix.QR

The scalar factors of the elementary reflectors

TaxonomicDistance - Class in smile.taxonomy

The distance between concepts in a taxonomy.

TaxonomicDistance(Taxonomy) - Constructor for class smile.taxonomy.TaxonomicDistance

Constructor.

Taxonomy - Class in smile.taxonomy

A taxonomy is a tree of terms (aka concept) where leaves must be named but intermediary nodes can be anonymous.

Taxonomy(String...) - Constructor for class smile.taxonomy.Taxonomy

Constructor.

TDistribution - Class in smile.stat.distribution

Student's t-distribution (or simply the t-distribution) is a probability distribution that arises in the problem of estimating the mean of a normally distributed population when the sample size is small.

TDistribution(int) - Constructor for class smile.stat.distribution.TDistribution

Constructor.

tension(double) - Method in class smile.plot.vega.Mark

Depending on the interpolation type, sets the tension parameter (for line and area marks).

Tensor - Class in smile.deep.tensor

A Tensor is a multi-dimensional array containing elements of a single data type.

Tensor(Tensor) - Constructor for class smile.deep.tensor.Tensor

Constructor.

Tensor.Options - Class in smile.deep.tensor

A class that encapsulates the construction axes of a Tensor.

Term - Interface in smile.data.formula

An abstract term in the formula.

terms() - Method in interface smile.nlp.Corpus

Returns the iterator over the terms in the corpus.

terms() - Method in class smile.nlp.SimpleCorpus

Terms - Interface in smile.data.formula

Predefined terms.

terrain(int) - Static method in interface smile.plot.swing.Palette

Generate terrain color palette.

terrain(int, float) - Static method in interface smile.plot.swing.Palette

Generate terrain color palette.

test(double[], double) - Static method in interface smile.stat.Hypothesis.t

Independent one-sample t-test whether the mean of a normally distributed population has a value specified in a null hypothesis.

test(double[], double) - Static method in class smile.stat.hypothesis.TTest

Independent one-sample t-test whether the mean of a normally distributed population has a value specified in a null hypothesis.

test(double[], double[]) - Static method in interface smile.stat.Hypothesis.cor

Pearson correlation test.

test(double[], double[]) - Static method in interface smile.stat.Hypothesis.F

Test if the arrays x and y have significantly different variances.

test(double[], double[]) - Static method in class smile.stat.hypothesis.FTest

Test if the arrays x and y have significantly different variances.

test(double[], double[]) - Static method in interface smile.stat.Hypothesis.KS

The two-sample KS test for the null hypothesis that the data sets are drawn from the same distribution.

test(double[], double[]) - Static method in class smile.stat.hypothesis.KSTest

The two-sample KS test for the null hypothesis that the data sets are drawn from the same distribution.

test(double[], double[]) - Static method in interface smile.stat.Hypothesis.t

Test if the arrays x and y have significantly different means.

test(double[], double[]) - Static method in class smile.stat.hypothesis.TTest

Test if the arrays x and y have significantly different means.

test(double[], double[], boolean) - Static method in class smile.stat.hypothesis.TTest

Test if the arrays x and y have significantly different means.

test(double[], double[], String) - Static method in interface smile.stat.Hypothesis.cor

Correlation test.

test(double[], double[], String) - Static method in interface smile.stat.Hypothesis.t

Test if the arrays x and y have significantly different means.

test(double[], Distribution) - Static method in interface smile.stat.Hypothesis.KS

The one-sample KS test for the null hypothesis that the data set x is drawn from the given distribution.

test(double[], Distribution) - Static method in class smile.stat.hypothesis.KSTest

The one-sample KS test for the null hypothesis that the data set x is drawn from the given distribution.

test(double, int) - Static method in interface smile.stat.Hypothesis.t

Test whether the Pearson correlation coefficient, the slope of a regression line, differs significantly from 0.

test(double, int) - Static method in class smile.stat.hypothesis.TTest

Test whether the Pearson correlation coefficient, the slope of a regression line, differs significantly from 0.

test(int[][]) - Static method in interface smile.stat.Hypothesis.chisq

Given a two-dimensional contingency table in the form of an array of integers, returns Chi-square test for independence.

test(int[][]) - Static method in class smile.stat.hypothesis.ChiSqTest

Independence test on a two-dimensional contingency table.

test(int[], double[]) - Static method in interface smile.stat.Hypothesis.chisq

One-sample chisq test.

test(int[], double[]) - Static method in class smile.stat.hypothesis.ChiSqTest

One-sample Pearson's chi-square test.

test(int[], double[]) - Static method in class smile.stat.hypothesis.FTest

One-way analysis of variance (ANOVA) between a categorical independent variable (with two or more categories) and a normally distributed interval dependent variable to test for differences in the means of the dependent variable broken down by the levels of the independent variable.

test(int[], double[], int) - Static method in interface smile.stat.Hypothesis.chisq

One-sample chisq test.

test(int[], double[], int) - Static method in class smile.stat.hypothesis.ChiSqTest

One-sample Pearson's chi-square test.

test(int[], int[]) - Static method in interface smile.stat.Hypothesis.chisq

Two-sample chisq test.

test(int[], int[]) - Static method in class smile.stat.hypothesis.ChiSqTest

Two-sample Pearson's chi-square test.

test(int[], int[], int) - Static method in interface smile.stat.Hypothesis.chisq

Two-sample chisq test.

test(int[], int[], int) - Static method in class smile.stat.hypothesis.ChiSqTest

Two-sample Pearson's chi-square test.

test(DataFrame) - Method in class smile.classification.AdaBoost

Test the model on a validation dataset.

test(DataFrame) - Method in class smile.classification.GradientTreeBoost

Test the model on a validation dataset.

test(DataFrame) - Method in class smile.classification.RandomForest

Test the model on a validation dataset.

test(DataFrame) - Method in class smile.regression.GradientTreeBoost

Test the model on a validation dataset.

test(DataFrame) - Method in class smile.regression.RandomForest

Test the model on a validation dataset.

testPaired(double[], double[]) - Static method in class smile.stat.hypothesis.TTest

Given the paired arrays x and y, test if they have significantly different means.

text - Variable in class smile.nlp.relevance.Relevance

The document to rank.

text() - Static method in interface smile.hash.SimHash

Returns the SimHash for string tokens.

text(Path) - Static method in class smile.math.matrix.fp32.SparseMatrix

Reads a sparse matrix from a text file.

text(Path) - Static method in class smile.math.matrix.SparseMatrix

Reads a sparse matrix from a text file.

Text - Class in smile.nlp

A minimal interface of text in the corpus.

Text(String) - Constructor for class smile.nlp.Text

Constructor.

Text(String, String) - Constructor for class smile.nlp.Text

Constructor.

Text(String, String, String) - Constructor for class smile.nlp.Text

Constructor.

TextPlot - Class in smile.plot.swing

The scatter plot of texts.

TextPlot(Label...) - Constructor for class smile.plot.swing.TextPlot

Constructor.

TextTerms - Interface in smile.nlp

The terms in a text.

tf(String) - Method in class smile.nlp.SimpleText

tf(String) - Method in interface smile.nlp.TextTerms

Returns the term frequency.

TFIDF - Class in smile.nlp.relevance

The tf-idf weight (term frequency-inverse document frequency) is a weight often used in information retrieval and text mining.

TFIDF() - Constructor for class smile.nlp.relevance.TFIDF

Constructor.

TFIDF(double) - Constructor for class smile.nlp.relevance.TFIDF

Constructor.

theta - Variable in class smile.stat.distribution.GammaDistribution

The scale parameter.

theta(double) - Method in class smile.plot.vega.Mark

For arc marks, sets the arc length in radians if theta2 is not specified, otherwise the start arc angle.

theta2(double) - Method in class smile.plot.vega.Mark

Sets the end angle of arc marks in radians.

theta2Offset(double) - Method in class smile.plot.vega.Mark

Sets the offset for theta2.

thetaOffset(double) - Method in class smile.plot.vega.Mark

Sets the offset for theta.

ThinPlateRadialBasis - Class in smile.math.rbf

Thin plate RBF.

ThinPlateRadialBasis() - Constructor for class smile.math.rbf.ThinPlateRadialBasis

Constructor.

ThinPlateRadialBasis(double) - Constructor for class smile.math.rbf.ThinPlateRadialBasis

Constructor.

ThinPlateSpline - Class in smile.math.kernel

The Thin Plate Spline kernel.

ThinPlateSpline(double, double, double) - Constructor for class smile.math.kernel.ThinPlateSpline

Constructor.

ThinPlateSplineKernel - Class in smile.math.kernel

The Thin Plate Spline kernel.

ThinPlateSplineKernel(double) - Constructor for class smile.math.kernel.ThinPlateSplineKernel

Constructor.

ThinPlateSplineKernel(double, double, double) - Constructor for class smile.math.kernel.ThinPlateSplineKernel

Constructor.

tickBand(String) - Method in class smile.plot.vega.Axis

For band scales, sets if ticks and grid lines should be placed at the "center" of a band or at the band "extent"s to indicate intervals.

tickCap(String) - Method in class smile.plot.vega.Axis

Sets the stroke cap for tick lines' ending style.

tickColor(String) - Method in class smile.plot.vega.Axis

Sets the color of the axis's tick.

tickCount(int) - Method in class smile.plot.vega.Axis

Sets a desired number of ticks, for axes visualizing quantitative scales.

tickCount(int) - Method in class smile.plot.vega.Legend

Sets the desired number of tick values for quantitative legends.

tickCount(String) - Method in class smile.plot.vega.Legend

Sets the desired number of tick values for quantitative legends.

ticks(boolean) - Method in class smile.plot.vega.Axis

Sets whether the axis should include ticks.

tiktoken(String, Pattern) - Static method in interface smile.llm.tokenizer.Tokenizer

Loads a tiktoken model with default BOS token () and EOS token ().

tiktoken(String, Pattern, String, String, String...) - Static method in interface smile.llm.tokenizer.Tokenizer

Loads a tiktoken model.

Tiktoken - Class in smile.llm.tokenizer

tiktoken is a fast BPE tokenizer by OpenAI.

Tiktoken(Pattern, Map<Bytes, Integer>, String, String, String...) - Constructor for class smile.llm.tokenizer.Tiktoken

Constructor.

time(String) - Static method in class smile.data.type.DataTypes

Time data type with customized format.

Time - Enum constant in enum class smile.data.type.DataType.ID

Time type ID.

TIME - Static variable in interface smile.util.Regex

Time regular expression pattern.

timeFormat(String) - Method in class smile.plot.vega.FormatConfig

Sets custom time format.

timeFormatType(String) - Method in class smile.plot.vega.FormatConfig

Sets custom time format type.

TimeFunction - Interface in smile.math

A time-dependent function.

TimeSeries - Interface in smile.timeseries

Time series utility functions.

TimeType - Class in smile.data.type

Time data type.

TimeType - Static variable in class smile.data.type.DataTypes

Time data type with ISO format.

TimeType(String) - Constructor for class smile.data.type.TimeType

Constructor.

timeUnit(String) - Method in class smile.plot.vega.FacetField

Sets the time unit for a temporal field.

timeUnit(String) - Method in class smile.plot.vega.Field

Sets the time unit for a temporal field.

timeUnit(String) - Method in class smile.plot.vega.Predicate

Sets the time unit for a temporal field.

timeUnit(String, String, String) - Method in class smile.plot.vega.Transform

Adds a time unit transform.

title - Variable in class smile.nlp.Text

The title of document;

title(String) - Method in class smile.plot.vega.Axis

Sets a descriptive title.

title(String) - Method in class smile.plot.vega.Concat

title(String) - Method in class smile.plot.vega.Facet

title(String) - Method in class smile.plot.vega.Field

Sets the title for the field.

title(String) - Method in class smile.plot.vega.Legend

Sets a descriptive title.

title(String) - Method in class smile.plot.vega.Repeat

title(String) - Method in class smile.plot.vega.VegaLite

Sets a descriptive title to a chart.

title(String) - Method in class smile.plot.vega.View

tm(BigMatrix) - Method in class smile.math.matrix.BigMatrix

Returns matrix multiplication A' * B.

tm(Matrix) - Method in class smile.math.matrix.fp32.Matrix

Returns matrix multiplication A' * B.

tm(Matrix) - Method in class smile.math.matrix.Matrix

Returns matrix multiplication A' * B.

to(Device) - Method in class smile.deep.Model

Moves the model to a device.

to(Device) - Method in class smile.deep.tensor.Tensor

Clone the tensor to a device.

to(Device) - Method in class smile.llm.PositionalEncoding

Moves the encoder to a device.

to(Device) - Method in class smile.llm.Transformer

Moves the model to a device.

to(Device, ScalarType) - Method in class smile.deep.tensor.Tensor

Clone the tensor to a device with a different data type.

to(ScalarType) - Method in class smile.deep.tensor.Tensor

Clone the tensor with a different data type.

TO - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

to.

toArray() - Method in interface smile.data.vector.Vector

Returns the array of elements.

toArray() - Method in class smile.graph.AdjacencyMatrix

Returns the adjacency matrix.

toArray() - Method in class smile.math.matrix.BigMatrix

Return the two-dimensional array of matrix.

toArray() - Method in class smile.math.matrix.fp32.Matrix

Return the two-dimensional array of matrix.

toArray() - Method in class smile.math.matrix.Matrix

Return the two-dimensional array of matrix.

toArray() - Method in class smile.sort.HeapSelect

Returns the array back the heap.

toArray() - Method in class smile.util.DoubleArrayList

Returns an array containing all the values in this list in proper sequence (from first to last value).

toArray() - Method in class smile.util.IntArrayList

Returns an array containing all the values in this list in proper sequence (from first to last value).

toArray() - Method in class smile.util.IntHashSet

Returns the elements as an array.

toArray(boolean, CategoricalEncoder, String...) - Method in interface smile.data.DataFrame

Return an array obtained by converting the columns in a data frame to numeric mode and then binding them together as the columns of a matrix.

toArray(boolean, CategoricalEncoder, String...) - Method in interface smile.data.Tuple

Return an array obtained by converting the fields to numeric mode.

toArray(double[]) - Method in class smile.util.DoubleArrayList

Returns an array containing all the values in this list in proper sequence (from first to last value).

toArray(int[]) - Method in class smile.util.IntArrayList

Returns an array containing all the values in this list in proper sequence (from first to last value).

toArray(String...) - Method in interface smile.data.DataFrame

Return an array obtained by converting the columns in a data frame to numeric mode and then binding them together as the columns of a matrix.

toArray(String...) - Method in interface smile.data.Tuple

Return an array obtained by converting the fields to numeric mode.

toArray(T[]) - Method in class smile.sort.HeapSelect

Returns the array back the heap.

toBufferedImage(int, int) - Method in class smile.plot.swing.Canvas

Exports the plot to an image.

toDate() - Method in interface smile.data.vector.Vector

Returns a vector of LocalDate.

toDate(String) - Method in interface smile.data.vector.StringVector

Returns a vector of LocalDate.

toDate(DateTimeFormatter) - Method in interface smile.data.vector.StringVector

Returns a vector of LocalDate.

toDateTime() - Method in interface smile.data.vector.Vector

Returns a vector of LocalDateTime.

toDateTime(String) - Method in interface smile.data.vector.StringVector

Returns a vector of LocalDateTime.

toDateTime(DateTimeFormatter) - Method in interface smile.data.vector.StringVector

Returns a vector of LocalDateTime.

toDoubleArray() - Method in interface smile.data.vector.BaseVector

Returns a double array of this vector.

toDoubleArray(double[]) - Method in interface smile.data.vector.BaseVector

Copies the vector value as double to the given array.

toeplitz(double[]) - Static method in class smile.math.matrix.BigMatrix

Returns a symmetric Toeplitz matrix in which each descending diagonal from left to right is constant.

toeplitz(double[]) - Static method in class smile.math.matrix.Matrix

Returns a symmetric Toeplitz matrix in which each descending diagonal from left to right is constant.

toeplitz(double[], double[]) - Static method in class smile.math.matrix.BigMatrix

Returns a Toeplitz matrix in which each descending diagonal from left to right is constant.

toeplitz(double[], double[]) - Static method in class smile.math.matrix.Matrix

Returns a Toeplitz matrix in which each descending diagonal from left to right is constant.

toeplitz(float[]) - Static method in class smile.math.matrix.fp32.Matrix

Returns a symmetric Toeplitz matrix in which each descending diagonal from left to right is constant.

toeplitz(float[], float[]) - Static method in class smile.math.matrix.fp32.Matrix

Returns a Toeplitz matrix in which each descending diagonal from left to right is constant.

ToFloatFunction<T> - Interface in smile.util

Represents a function that produces a float-valued result.

toIntArray() - Method in interface smile.data.vector.BaseVector

Returns an int array of this vector.

toIntArray(int[]) - Method in interface smile.data.vector.BaseVector

Copies the vector value as int to the given array.

tokenize(String) - Method in class smile.llm.tokenizer.SentencePiece

tokenize(String) - Method in class smile.llm.tokenizer.Tiktoken

tokenize(String) - Method in interface smile.llm.tokenizer.Tokenizer

Segments text into tokens.

Tokenizer - Interface in smile.llm.tokenizer

Tokenizing and encoding/decoding text.

Tokenizer - Interface in smile.nlp.tokenizer

A token is a string of characters, categorized according to the rules as a symbol.

toList() - Method in interface smile.data.DataFrame

Returns the List of rows.

toList() - Method in interface smile.data.Dataset

Returns the List of data items.

toMatrix() - Method in interface smile.data.BinarySparseDataset

Returns the Harwell-Boeing column-compressed sparse matrix.

toMatrix() - Method in interface smile.data.DataFrame

Return a matrix obtained by converting all the variables in a data frame to numeric mode and then binding them together as the columns of a matrix.

toMatrix() - Method in interface smile.data.SparseDataset

Convert into Harwell-Boeing column-compressed sparse matrix format.

toMatrix() - Method in class smile.graph.AdjacencyList

toMatrix() - Method in class smile.graph.AdjacencyMatrix

toMatrix() - Method in interface smile.graph.Graph

Returns the (dense or sparse) matrix representation of the graph.

toMatrix(boolean, CategoricalEncoder, String) - Method in interface smile.data.DataFrame

Return a matrix obtained by converting all the variables in a data frame to numeric mode and then binding them together as the columns of a matrix.

toNode(Node, Node) - Method in class smile.base.cart.NominalSplit

toNode(Node, Node) - Method in class smile.base.cart.OrdinalSplit

toNode(Node, Node) - Method in class smile.base.cart.Split

Returns an internal node with the feature, value, and score of this split.

toolbar() - Method in class smile.plot.swing.Plot

Returns an optional list of components in tool bar to control the plot.

tooltip(boolean) - Method in class smile.plot.vega.Mark

Turns on/off the tooltip.

tooltip(double[]) - Method in class smile.plot.swing.BoxPlot

tooltip(double[]) - Method in class smile.plot.swing.Heatmap

tooltip(double[]) - Method in class smile.plot.swing.Hexmap

tooltip(double[]) - Method in class smile.plot.swing.Plot

Returns a optional tool tip for the object at given coordinates.

tooltip(String) - Method in class smile.plot.vega.Mark

Sets the tooltip text string to show upon mouse hover or which fields should the tooltip be derived from.

tooltipFormat() - Method in class smile.plot.vega.Config

Define custom format configuration for tooltips.

topk(int) - Method in class smile.deep.tensor.Tensor

Returns the k largest elements.

topk(int, int, boolean, boolean) - Method in class smile.deep.tensor.Tensor

Returns the k largest elements along a given dimension.

topo(int) - Static method in interface smile.plot.swing.Palette

Generate topo color palette.

topo(int, float) - Static method in interface smile.plot.swing.Palette

Generate topo color palette.

topojson(String, String, String) - Method in class smile.plot.vega.Data

Loads a JSON file using the TopoJSON format.

toPrettyString() - Method in class smile.plot.vega.Axis

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.Background

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.Config

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.Data

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.DensityTransform

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.FacetField

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.Field

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.FormatConfig

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.ImputeTransform

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.Legend

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.LoessTransform

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.LookupData

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.Mark

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.PivotTransform

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.Projection

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.QuantileTransform

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.RegressionTransform

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.StackTransform

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.Transform

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.VegaLite

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.ViewConfig

Returns the specification in pretty print.

toPrettyString() - Method in class smile.plot.vega.WindowTransform

Returns the specification in pretty print.

toString() - Method in class smile.association.AssociationRule

toString() - Method in class smile.association.ItemSet

toString() - Method in class smile.base.cart.CART

Returns a text representation of the tree in R's rpart format.

toString() - Method in class smile.base.cart.Split

toString() - Method in class smile.base.mlp.HiddenLayer

toString() - Method in class smile.base.mlp.HiddenLayerBuilder

toString() - Method in class smile.base.mlp.InputLayer

toString() - Method in class smile.base.mlp.MultilayerPerceptron

toString() - Method in class smile.base.mlp.optimizer.Adam

toString() - Method in class smile.base.mlp.optimizer.RMSProp

toString() - Method in class smile.base.mlp.optimizer.SGD

toString() - Method in class smile.base.mlp.OutputLayer

toString() - Method in class smile.base.mlp.OutputLayerBuilder

toString() - Method in class smile.base.svm.KernelMachine

toString() - Method in class smile.classification.IsotonicRegressionScaling

toString() - Method in class smile.clustering.CentroidClustering

toString() - Method in class smile.clustering.linkage.CompleteLinkage

toString() - Method in class smile.clustering.linkage.SingleLinkage

toString() - Method in class smile.clustering.linkage.UPGMALinkage

toString() - Method in class smile.clustering.linkage.UPGMCLinkage

toString() - Method in class smile.clustering.linkage.WardLinkage

toString() - Method in class smile.clustering.linkage.WPGMALinkage

toString() - Method in class smile.clustering.linkage.WPGMCLinkage

toString() - Method in class smile.clustering.MEC

toString() - Method in class smile.clustering.PartitionClustering

toString() - Method in class smile.data.AbstractTuple

toString() - Method in class smile.data.formula.AbstractBiFunction

toString() - Method in class smile.data.formula.AbstractFunction

toString() - Method in class smile.data.formula.Date

toString() - Method in class smile.data.formula.FactorCrossing

toString() - Method in class smile.data.formula.FactorInteraction

toString() - Method in class smile.data.formula.Formula

toString() - Method in class smile.data.formula.Operator

toString() - Method in class smile.data.IndexDataFrame

toString() - Method in class smile.data.measure.IntervalScale

toString() - Method in class smile.data.measure.NominalScale

toString() - Method in class smile.data.measure.OrdinalScale

toString() - Method in class smile.data.measure.RatioScale

toString() - Method in record class smile.data.SampleInstance

Returns a string representation of this record class.

toString() - Method in class smile.data.SQL

toString() - Method in class smile.data.transform.ColumnTransform

toString() - Method in class smile.data.type.ArrayType

toString() - Method in class smile.data.type.BooleanType

toString() - Method in class smile.data.type.ByteType

toString() - Method in class smile.data.type.CharType

toString() - Method in class smile.data.type.DateTimeType

toString() - Method in class smile.data.type.DateType

toString() - Method in class smile.data.type.DecimalType

toString() - Method in class smile.data.type.DoubleType

toString() - Method in class smile.data.type.FloatType

toString() - Method in class smile.data.type.IntegerType

toString() - Method in class smile.data.type.LongType

toString() - Method in class smile.data.type.ObjectType

toString() - Method in class smile.data.type.ShortType

toString() - Method in class smile.data.type.StringType

toString() - Method in class smile.data.type.StructField

toString() - Method in class smile.data.type.StructType

toString() - Method in class smile.data.type.TimeType

toString() - Method in class smile.deep.layer.LayerBlock

toString() - Method in class smile.deep.metric.Accuracy

toString() - Method in class smile.deep.metric.Precision

toString() - Method in class smile.deep.metric.Recall

toString() - Method in class smile.deep.Model

toString() - Method in record class smile.deep.SampleBatch

Returns a string representation of this record class.

toString() - Method in class smile.deep.tensor.Device

toString() - Method in class smile.deep.tensor.Tensor

toString() - Method in class smile.feature.imputation.SimpleImputer

toString() - Method in class smile.feature.selection.InformationValue

toString() - Method in class smile.feature.selection.SignalNoiseRatio

toString() - Method in class smile.feature.selection.SumSquaresRatio

toString() - Method in class smile.feature.transform.Normalizer

toString() - Method in class smile.gap.BitString

toString() - Method in class smile.glm.GLM

toString() - Method in class smile.interpolation.BicubicInterpolation

toString() - Method in class smile.interpolation.BilinearInterpolation

toString() - Method in class smile.interpolation.CubicSplineInterpolation1D

toString() - Method in class smile.interpolation.CubicSplineInterpolation2D

toString() - Method in class smile.interpolation.KrigingInterpolation

toString() - Method in class smile.interpolation.KrigingInterpolation1D

toString() - Method in class smile.interpolation.KrigingInterpolation2D

toString() - Method in class smile.interpolation.LaplaceInterpolation

toString() - Method in class smile.interpolation.LinearInterpolation

toString() - Method in class smile.interpolation.RBFInterpolation

toString() - Method in class smile.interpolation.RBFInterpolation1D

toString() - Method in class smile.interpolation.RBFInterpolation2D

toString() - Method in class smile.interpolation.ShepardInterpolation

toString() - Method in class smile.interpolation.ShepardInterpolation1D

toString() - Method in class smile.interpolation.ShepardInterpolation2D

toString() - Method in class smile.interpolation.variogram.ExponentialVariogram

toString() - Method in class smile.interpolation.variogram.GaussianVariogram

toString() - Method in class smile.interpolation.variogram.PowerVariogram

toString() - Method in class smile.interpolation.variogram.SphericalVariogram

toString() - Method in record class smile.llm.Transformer.Options

Returns a string representation of this record class.

toString() - Method in class smile.math.Complex

toString() - Method in class smile.math.distance.ChebyshevDistance

toString() - Method in class smile.math.distance.CorrelationDistance

toString() - Method in class smile.math.distance.DynamicTimeWarping

toString() - Method in class smile.math.distance.EditDistance

toString() - Method in class smile.math.distance.EuclideanDistance

toString() - Method in class smile.math.distance.HammingDistance

toString() - Method in class smile.math.distance.JaccardDistance

toString() - Method in class smile.math.distance.JensenShannonDistance

toString() - Method in class smile.math.distance.LeeDistance

toString() - Method in class smile.math.distance.MahalanobisDistance

toString() - Method in class smile.math.distance.ManhattanDistance

toString() - Method in class smile.math.distance.MinkowskiDistance

toString() - Method in class smile.math.distance.SparseChebyshevDistance

toString() - Method in class smile.math.distance.SparseEuclideanDistance

toString() - Method in class smile.math.distance.SparseManhattanDistance

toString() - Method in class smile.math.distance.SparseMinkowskiDistance

toString() - Method in class smile.math.kernel.BinarySparseLinearKernel

toString() - Method in class smile.math.kernel.Gaussian

toString() - Method in class smile.math.kernel.HellingerKernel

toString() - Method in class smile.math.kernel.HyperbolicTangent

toString() - Method in class smile.math.kernel.Laplacian

toString() - Method in class smile.math.kernel.LinearKernel

toString() - Method in class smile.math.kernel.Matern

toString() - Method in class smile.math.kernel.PearsonKernel

toString() - Method in class smile.math.kernel.Polynomial

toString() - Method in class smile.math.kernel.SparseLinearKernel

toString() - Method in class smile.math.kernel.ThinPlateSpline

toString() - Method in class smile.math.matrix.fp32.IMatrix

toString() - Method in class smile.math.matrix.fp32.SparseMatrix.Entry

toString() - Method in class smile.math.matrix.IMatrix

toString() - Method in class smile.math.matrix.SparseMatrix.Entry

toString() - Method in class smile.math.rbf.GaussianRadialBasis

toString() - Method in class smile.math.rbf.InverseMultiquadricRadialBasis

toString() - Method in class smile.math.rbf.MultiquadricRadialBasis

toString() - Method in class smile.math.rbf.ThinPlateRadialBasis

toString() - Method in class smile.neighbor.BKTree

toString() - Method in class smile.neighbor.CoverTree

toString() - Method in class smile.neighbor.KDTree

toString() - Method in class smile.neighbor.LinearSearch

toString() - Method in class smile.neighbor.LSH

toString() - Method in class smile.neighbor.MPLSH

toString() - Method in class smile.neighbor.Neighbor

toString() - Method in class smile.nlp.Bigram

toString() - Method in class smile.nlp.collocation.Bigram

toString() - Method in class smile.nlp.collocation.NGram

toString() - Method in class smile.nlp.NGram

toString() - Method in class smile.nlp.SimpleText

toString() - Method in class smile.plot.swing.Base

toString() - Method in class smile.plot.vega.Axis

toString() - Method in class smile.plot.vega.Background

toString() - Method in class smile.plot.vega.Config

toString() - Method in class smile.plot.vega.Data

toString() - Method in class smile.plot.vega.DensityTransform

toString() - Method in class smile.plot.vega.FacetField

toString() - Method in class smile.plot.vega.Field

toString() - Method in class smile.plot.vega.FormatConfig

toString() - Method in class smile.plot.vega.ImputeTransform

toString() - Method in class smile.plot.vega.Legend

toString() - Method in class smile.plot.vega.LoessTransform

toString() - Method in class smile.plot.vega.LookupData

toString() - Method in class smile.plot.vega.Mark

toString() - Method in class smile.plot.vega.PivotTransform

toString() - Method in class smile.plot.vega.Projection

toString() - Method in class smile.plot.vega.QuantileTransform

toString() - Method in class smile.plot.vega.RegressionTransform

toString() - Method in record class smile.plot.vega.SortField

Returns a string representation of this record class.

toString() - Method in class smile.plot.vega.StackTransform

toString() - Method in class smile.plot.vega.Transform

toString() - Method in class smile.plot.vega.VegaLite

toString() - Method in class smile.plot.vega.ViewConfig

toString() - Method in class smile.plot.vega.WindowTransform

toString() - Method in record class smile.plot.vega.WindowTransformField

Returns a string representation of this record class.

toString() - Method in class smile.regression.GaussianProcessRegression.JointPrediction

toString() - Method in class smile.regression.GaussianProcessRegression

toString() - Method in class smile.regression.LinearModel

toString() - Method in class smile.sequence.CRFLabeler

toString() - Method in class smile.sequence.HMM

toString() - Method in class smile.sequence.HMMLabeler

toString() - Method in class smile.stat.distribution.BernoulliDistribution

toString() - Method in class smile.stat.distribution.BetaDistribution

toString() - Method in class smile.stat.distribution.BinomialDistribution

toString() - Method in class smile.stat.distribution.ChiSquareDistribution

toString() - Method in class smile.stat.distribution.DiscreteMixture

toString() - Method in class smile.stat.distribution.EmpiricalDistribution

toString() - Method in class smile.stat.distribution.ExponentialDistribution

toString() - Method in class smile.stat.distribution.FDistribution

toString() - Method in class smile.stat.distribution.GammaDistribution

toString() - Method in class smile.stat.distribution.GaussianDistribution

toString() - Method in class smile.stat.distribution.GeometricDistribution

toString() - Method in class smile.stat.distribution.HyperGeometricDistribution

toString() - Method in class smile.stat.distribution.LogisticDistribution

toString() - Method in class smile.stat.distribution.LogNormalDistribution

toString() - Method in class smile.stat.distribution.Mixture

toString() - Method in class smile.stat.distribution.MultivariateGaussianDistribution

toString() - Method in class smile.stat.distribution.MultivariateMixture

toString() - Method in class smile.stat.distribution.NegativeBinomialDistribution

toString() - Method in class smile.stat.distribution.PoissonDistribution

toString() - Method in class smile.stat.distribution.ShiftedGeometricDistribution

toString() - Method in class smile.stat.distribution.TDistribution

toString() - Method in class smile.stat.distribution.WeibullDistribution

toString() - Method in class smile.stat.hypothesis.ChiSqTest

toString() - Method in class smile.stat.hypothesis.CorTest

toString() - Method in class smile.stat.hypothesis.FTest

toString() - Method in class smile.stat.hypothesis.KSTest

toString() - Method in class smile.stat.hypothesis.TTest

toString() - Method in class smile.taxonomy.Concept

toString() - Method in class smile.taxonomy.TaxonomicDistance

toString() - Method in class smile.timeseries.AR

toString() - Method in class smile.timeseries.ARMA

toString() - Method in class smile.timeseries.BoxTest

toString() - Method in class smile.util.Array2D

toString() - Method in record class smile.util.Bytes

Returns a string representation of this record class.

toString() - Method in class smile.util.DoubleArrayList

toString() - Method in class smile.util.IntArray2D

toString() - Method in class smile.util.IntArrayList

toString() - Method in record class smile.util.IntPair

Returns a string representation of this record class.

toString() - Method in class smile.util.SparseArray.Entry

toString() - Method in class smile.util.SparseArray

toString() - Method in record class smile.util.Tuple2

Returns a string representation of this record class.

toString() - Method in class smile.validation.ClassificationMetrics

toString() - Method in class smile.validation.ClassificationValidation

toString() - Method in class smile.validation.ClassificationValidations

toString() - Method in class smile.validation.metric.Accuracy

toString() - Method in class smile.validation.metric.AdjustedMutualInformation

toString() - Method in class smile.validation.metric.AdjustedRandIndex

toString() - Method in class smile.validation.metric.AUC

toString() - Method in class smile.validation.metric.ConfusionMatrix

toString() - Method in class smile.validation.metric.Error

toString() - Method in class smile.validation.metric.Fallout

toString() - Method in class smile.validation.metric.FDR

toString() - Method in class smile.validation.metric.FScore

toString() - Method in class smile.validation.metric.LogLoss

toString() - Method in class smile.validation.metric.MAD

toString() - Method in class smile.validation.metric.MatthewsCorrelation

toString() - Method in class smile.validation.metric.MSE

toString() - Method in class smile.validation.metric.MutualInformation

toString() - Method in class smile.validation.metric.NormalizedMutualInformation

toString() - Method in class smile.validation.metric.Precision

toString() - Method in class smile.validation.metric.R2

toString() - Method in class smile.validation.metric.RandIndex

toString() - Method in class smile.validation.metric.Recall

toString() - Method in class smile.validation.metric.RMSE

toString() - Method in class smile.validation.metric.RSS

toString() - Method in class smile.validation.metric.Sensitivity

toString() - Method in class smile.validation.metric.Specificity

toString() - Method in class smile.validation.RegressionMetrics

toString() - Method in class smile.validation.RegressionValidation

toString() - Method in class smile.validation.RegressionValidations

toString() - Method in record class smile.vision.layer.Conv2dNormActivation.Options

Returns a string representation of this record class.

toString() - Method in class smile.vision.layer.Conv2dNormActivation

toString() - Method in record class smile.vision.layer.MBConvConfig

Returns a string representation of this record class.

toString(boolean) - Method in class smile.math.matrix.fp32.IMatrix

Returns the string representation of matrix.

toString(boolean) - Method in class smile.math.matrix.IMatrix

Returns the string representation of matrix.

toString(boolean) - Method in class smile.util.Array2D

Returns the string representation of matrix.

toString(boolean) - Method in class smile.util.IntArray2D

Returns the string representation of matrix.

toString(int) - Method in interface smile.data.DataFrame

Returns the string representation of top rows.

toString(int) - Method in interface smile.data.Dataset

Returns the string representation of the dataset.

toString(int) - Method in class smile.data.measure.CategoricalMeasure

Returns the string value of a level.

toString(int) - Method in interface smile.data.Tuple

Returns the string representation of the value at position i.

toString(int) - Method in interface smile.data.vector.BooleanVector

Returns the string representation of vector.

toString(int) - Method in interface smile.data.vector.ByteVector

Returns the string representation of vector.

toString(int) - Method in interface smile.data.vector.CharVector

Returns the string representation of vector.

toString(int) - Method in interface smile.data.vector.DoubleVector

Returns the string representation of vector.

toString(int) - Method in interface smile.data.vector.FloatVector

Returns the string representation of vector.

toString(int) - Method in interface smile.data.vector.IntVector

Returns the string representation of vector.

toString(int) - Method in interface smile.data.vector.LongVector

Returns the string representation of vector.

toString(int) - Method in interface smile.data.vector.ShortVector

Returns the string representation of vector.

toString(int) - Method in interface smile.data.vector.StringVector

Returns the string representation of vector.

toString(int) - Method in interface smile.data.vector.Vector

Returns the string representation of vector.

toString(int, boolean) - Method in interface smile.data.DataFrame

Returns the string representation of top rows.

toString(int, int) - Method in interface smile.data.DataFrame

Returns the string representation of the value at position (i, j).

toString(int, int) - Method in class smile.math.matrix.fp32.IMatrix

Returns the string representation of matrix.

toString(int, int) - Method in class smile.math.matrix.IMatrix

Returns the string representation of matrix.

toString(int, int) - Method in class smile.util.Array2D

Returns the string representation of matrix.

toString(int, int) - Method in class smile.util.IntArray2D

Returns the string representation of matrix.

toString(int, String) - Method in interface smile.data.DataFrame

Returns the string representation of the field value.

toString(Object) - Method in class smile.data.measure.CategoricalMeasure

toString(Object) - Method in interface smile.data.measure.Measure

Returns the string representation of an object in the measure.

toString(Object) - Method in class smile.data.measure.NumericalMeasure

toString(Object) - Method in class smile.data.type.ArrayType

toString(Object) - Method in interface smile.data.type.DataType

Returns the string representation of a value of the type.

toString(Object) - Method in class smile.data.type.DateTimeType

toString(Object) - Method in class smile.data.type.DateType

toString(Object) - Method in class smile.data.type.DoubleType

toString(Object) - Method in class smile.data.type.FloatType

toString(Object) - Method in class smile.data.type.ObjectType

toString(Object) - Method in class smile.data.type.StructField

Returns the string representation of the field object.

toString(Object) - Method in class smile.data.type.StructType

toString(Object) - Method in class smile.data.type.TimeType

toString(String) - Method in interface smile.data.Tuple

Returns the string representation of the field value.

toString(StructType, boolean) - Method in class smile.base.cart.InternalNode

Returns the string representation of branch.

toString(StructType, boolean) - Method in class smile.base.cart.NominalNode

toString(StructType, boolean) - Method in class smile.base.cart.OrdinalNode

toString(StructType, StructField, InternalNode, int, BigInteger, List<String>) - Method in class smile.base.cart.DecisionNode

toString(StructType, StructField, InternalNode, int, BigInteger, List<String>) - Method in class smile.base.cart.InternalNode

toString(StructType, StructField, InternalNode, int, BigInteger, List<String>) - Method in interface smile.base.cart.Node

Adds the string representation (R's rpart format) to a collection.

toString(StructType, StructField, InternalNode, int, BigInteger, List<String>) - Method in class smile.base.cart.RegressionNode

toString(InformationValue[]) - Static method in class smile.feature.selection.InformationValue

Returns a string representation of the array of information values.

toStringArray() - Method in interface smile.data.vector.BaseVector

Returns a string array of this vector.

toStringArray(String[]) - Method in interface smile.data.vector.BaseVector

Copies the vector value as string to the given array.

toStrings(int) - Method in interface smile.data.DataFrame

Returns the string representation of top rows.

toStrings(int, boolean) - Method in interface smile.data.DataFrame

Returns the string representation of top rows.

toTensor(float[], float[], BufferedImage...) - Method in interface smile.vision.transform.Transform

Returns the tensor with NCHW shape [samples, channels, height, width] of the images.

toTime() - Method in interface smile.data.vector.Vector

Returns a vector of LocalTime.

toTime(String) - Method in interface smile.data.vector.StringVector

Returns a vector of LocalTime.

toTime(DateTimeFormatter) - Method in interface smile.data.vector.StringVector

Returns a vector of LocalDate.

toTransform(InformationValue[]) - Static method in class smile.feature.selection.InformationValue

Returns the data transformation that covert feature value to its weight of evidence.

Tournament(int, double) - Static method in interface smile.gap.Selection

Tournament Selection.

tpmv(Layout, UPLO, Transpose, Diag, int, double[], double[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a triangular packed matrix.

tpmv(Layout, UPLO, Transpose, Diag, int, double[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

tpmv(Layout, UPLO, Transpose, Diag, int, float[], float[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a triangular packed matrix.

tpmv(Layout, UPLO, Transpose, Diag, int, float[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

tpmv(Layout, UPLO, Transpose, Diag, int, DoubleBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a triangular packed matrix.

tpmv(Layout, UPLO, Transpose, Diag, int, DoubleBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

tpmv(Layout, UPLO, Transpose, Diag, int, FloatBuffer, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a triangular packed matrix.

tpmv(Layout, UPLO, Transpose, Diag, int, FloatBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

trace() - Method in class smile.math.matrix.fp32.IMatrix

Returns the matrix trace.

trace() - Method in class smile.math.matrix.IMatrix

Returns the matrix trace.

train() - Method in class smile.deep.Model

Sets the model in the training mode.

train(int, Optimizer, Loss, Dataset) - Method in class smile.deep.Model

Trains the model.

train(int, Optimizer, Loss, Dataset, Dataset, String, Metric...) - Method in class smile.deep.Model

Trains the model.

transform() - Method in class smile.plot.vega.VegaLite

Returns the data transformation object.

transform() - Method in class smile.vision.VisionModel

Returns the associated image transform.

transform(double[]) - Method in class smile.base.mlp.HiddenLayer

transform(double[]) - Method in class smile.base.mlp.InputLayer

transform(double[]) - Method in class smile.base.mlp.Layer

The activation or output function.

transform(double[]) - Method in class smile.base.mlp.OutputLayer

transform(double[]) - Method in class smile.wavelet.Wavelet

Discrete wavelet transform.

Transform - Class in smile.plot.vega

View-level data transformations such as filter and new field calculation.

Transform - Interface in smile.data.transform

Data transformation interface.

Transform - Interface in smile.vision.transform

Transformation from image to tensor.

Transformer - Class in smile.llm

A transformer is a deep learning architecture developed based on the multi-head attention mechanism, proposed in a 2017 paper "Attention Is All You Need".

Transformer(int) - Constructor for class smile.llm.Transformer

Creates a Transformer model with default architecture configuration.

Transformer(Transformer.Options) - Constructor for class smile.llm.Transformer

Creates a Transformer model with custom architecture configuration.

Transformer.Options - Record Class in smile.llm

Transformer architecture configuration.

translate(double) - Method in class smile.plot.vega.Axis

Sets the coordinate space translation offset for axis layout.

translate(double, double) - Method in class smile.plot.vega.Projection

Sets the projection's translation offset.

transpose() - Method in class smile.math.matrix.BigMatrix

Returns the transpose of matrix.

transpose() - Method in class smile.math.matrix.fp32.Matrix

Returns the transpose of matrix.

transpose() - Method in class smile.math.matrix.fp32.SparseMatrix

Returns the transpose of matrix.

transpose() - Method in class smile.math.matrix.Matrix

Returns the transpose of matrix.

transpose() - Method in class smile.math.matrix.SparseMatrix

Returns the transpose of matrix.

transpose(boolean) - Method in class smile.math.matrix.BigMatrix

Returns the transpose of matrix.

transpose(boolean) - Method in class smile.math.matrix.fp32.Matrix

Returns the transpose of matrix.

transpose(boolean) - Method in class smile.math.matrix.Matrix

Returns the transpose of matrix.

transpose(double[][]) - Static method in class smile.math.MathEx

Returns the matrix transpose.

transpose(long, long) - Method in class smile.deep.tensor.Tensor

Returns a tensor that is a transposed version of input.

Transpose - Enum Class in smile.math.blas

Matrix transpose.

TRANSPOSE - Enum constant in enum class smile.math.blas.Transpose

Transpose operation on the matrix.

tree - Variable in class smile.classification.RandomForest.Model

The decision tree.

tree - Variable in class smile.regression.RandomForest.Model

The decision tree.

tree() - Method in class smile.clustering.HierarchicalClustering

Returns an n-1 by 2 matrix of which row i describes the merging of clusters at step i of the clustering.

trees() - Method in class smile.anomaly.IsolationForest

Returns the isolation trees in the model.

trees() - Method in class smile.classification.AdaBoost

Returns the decision trees.

trees() - Method in class smile.classification.GradientTreeBoost

Returns the regression trees.

trees() - Method in class smile.classification.RandomForest

trees() - Method in interface smile.feature.importance.TreeSHAP

Returns the decision trees.

trees() - Method in class smile.regression.GradientTreeBoost

trees() - Method in class smile.regression.RandomForest

TreeSHAP - Interface in smile.feature.importance

SHAP of ensemble tree methods.

triangular() - Method in class smile.math.matrix.BigMatrix

Gets the flag if a triangular matrix has unit diagonal elements.

triangular() - Method in class smile.math.matrix.fp32.Matrix

Gets the flag if a triangular matrix has unit diagonal elements.

triangular() - Method in class smile.math.matrix.Matrix

Gets the flag if a triangular matrix has unit diagonal elements.

triangular(Diag) - Method in class smile.math.matrix.BigMatrix

Sets/unsets if the matrix is triangular.

triangular(Diag) - Method in class smile.math.matrix.fp32.Matrix

Sets/unsets if the matrix is triangular.

triangular(Diag) - Method in class smile.math.matrix.Matrix

Sets/unsets if the matrix is triangular.

Trie<K,V> - Class in smile.nlp

A trie, also called digital tree or prefix tree, is an ordered tree data structure that is used to store a dynamic set or associative array where the keys are usually strings.

Trie() - Constructor for class smile.nlp.Trie

Constructor.

Trie(int) - Constructor for class smile.nlp.Trie

Constructor.

Trie.Node - Class in smile.nlp

The nodes in the trie.

trim() - Method in class smile.util.DoubleArrayList

Trims the capacity to be the list's current size.

trim() - Method in class smile.util.IntArrayList

Trims the capacity to be the list's current size.

trim(int) - Method in class smile.classification.AdaBoost

Trims the tree model set to a smaller size in case of over-fitting.

trim(int) - Method in class smile.classification.GradientTreeBoost

Trims the tree model set to a smaller size in case of over-fitting.

trim(int) - Method in class smile.classification.RandomForest

Trims the tree model set to a smaller size in case of over-fitting.

trim(int) - Method in class smile.regression.GradientTreeBoost

Trims the tree model set to a smaller size in case of over-fitting.

trim(int) - Method in class smile.regression.RandomForest

Trims the tree model set to a smaller size in case of over-fitting.

tripleMarginRanking(Tensor, Tensor, Tensor) - Static method in interface smile.deep.Loss

Triplet Margin Ranking Loss Function.

trmv(Layout, UPLO, Transpose, Diag, int, double[], int, double[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a triangular matrix.

trmv(Layout, UPLO, Transpose, Diag, int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

trmv(Layout, UPLO, Transpose, Diag, int, float[], int, float[], int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a triangular matrix.

trmv(Layout, UPLO, Transpose, Diag, int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

trmv(Layout, UPLO, Transpose, Diag, int, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a triangular matrix.

trmv(Layout, UPLO, Transpose, Diag, int, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

trmv(Layout, UPLO, Transpose, Diag, int, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a triangular matrix.

trmv(Layout, UPLO, Transpose, Diag, int, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

trmv(Layout, UPLO, Transpose, Diag, int, DoublePointer, int, DoublePointer, int) - Method in interface smile.math.blas.BLAS

Performs the matrix-vector operation using a triangular matrix.

trmv(Layout, UPLO, Transpose, Diag, int, DoublePointer, int, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

trtrs(Layout, UPLO, Transpose, Diag, int, int, double[], int, double[], int) - Method in interface smile.math.blas.LAPACK

Solves a triangular system of the form

trtrs(Layout, UPLO, Transpose, Diag, int, int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS

trtrs(Layout, UPLO, Transpose, Diag, int, int, float[], int, float[], int) - Method in interface smile.math.blas.LAPACK

Solves a triangular system of the form

trtrs(Layout, UPLO, Transpose, Diag, int, int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS

trtrs(Layout, UPLO, Transpose, Diag, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a triangular system of the form

trtrs(Layout, UPLO, Transpose, Diag, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

trtrs(Layout, UPLO, Transpose, Diag, int, int, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK

Solves a triangular system of the form

trtrs(Layout, UPLO, Transpose, Diag, int, int, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS

trtrs(Layout, UPLO, Transpose, Diag, int, int, DoublePointer, int, DoublePointer, int) - Method in interface smile.math.blas.LAPACK

Solves a triangular system of the form

trtrs(Layout, UPLO, Transpose, Diag, int, int, DoublePointer, int, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS

trueChild() - Method in class smile.base.cart.InternalNode

Returns the true branch child.

truth - Variable in class smile.validation.ClassificationValidation

The true class labels of validation data.

truth - Variable in class smile.validation.RegressionValidation

The true response variable of validation data.

TSNE - Class in smile.manifold

The t-distributed stochastic neighbor embedding.

TSNE(double[][], int) - Constructor for class smile.manifold.TSNE

Constructor.

TSNE(double[][], int, double, double, int) - Constructor for class smile.manifold.TSNE

Constructor.

tsv(String, Map<String, String>) - Method in class smile.plot.vega.Data

Loads a tab-separated values (TSV) file

tt(BigMatrix) - Method in class smile.math.matrix.BigMatrix

Returns matrix multiplication A' * B'.

tt(Matrix) - Method in class smile.math.matrix.fp32.Matrix

Returns matrix multiplication A' * B'.

tt(Matrix) - Method in class smile.math.matrix.Matrix

Returns matrix multiplication A' * B'.

ttest() - Method in class smile.regression.LinearModel

Returns the t-test of the coefficients (including intercept).

ttest() - Method in class smile.timeseries.AR

Returns the t-test of the coefficients (including intercept).

ttest() - Method in class smile.timeseries.ARMA

Returns the t-test of the coefficients (including intercept).

TTest - Class in smile.stat.hypothesis

Student's t test.

TTest(String, double, double, double) - Constructor for class smile.stat.hypothesis.TTest

Constructor.

Tuple - Interface in smile.data

A tuple is an immutable finite ordered list (sequence) of elements.

Tuple2<T1,T2> - Record Class in smile.util

A tuple of 2 elements.

Tuple2(T1, T2) - Constructor for record class smile.util.Tuple2

Creates an instance of a Tuple2 record class.

TURQUOISE - Static variable in interface smile.plot.swing.Palette

tv(double[]) - Method in class smile.math.matrix.IMatrix

Returns Matrix-vector multiplication A' * x.

tv(double[], double[]) - Method in class smile.math.matrix.IMatrix

Matrix-vector multiplication y = A' * x.

tv(double[], int, int) - Method in class smile.math.matrix.BandMatrix

tv(double[], int, int) - Method in class smile.math.matrix.BigMatrix

tv(double[], int, int) - Method in class smile.math.matrix.IMatrix

Matrix-vector multiplication A' * x.

tv(double[], int, int) - Method in class smile.math.matrix.Matrix

tv(double[], int, int) - Method in class smile.math.matrix.SparseMatrix

tv(double[], int, int) - Method in class smile.math.matrix.SymmMatrix

tv(double, double[], double, double[]) - Method in class smile.math.matrix.IMatrix

Matrix-vector multiplication.

tv(float[]) - Method in class smile.math.matrix.fp32.IMatrix

Returns Matrix-vector multiplication A' * x.

tv(float[], float[]) - Method in class smile.math.matrix.fp32.IMatrix

Matrix-vector multiplication y = A' * x.

tv(float[], int, int) - Method in class smile.math.matrix.fp32.BandMatrix

tv(float[], int, int) - Method in class smile.math.matrix.fp32.IMatrix

Matrix-vector multiplication A' * x.

tv(float[], int, int) - Method in class smile.math.matrix.fp32.Matrix

tv(float[], int, int) - Method in class smile.math.matrix.fp32.SparseMatrix

tv(float[], int, int) - Method in class smile.math.matrix.fp32.SymmMatrix

tv(float, float[], float, float[]) - Method in class smile.math.matrix.fp32.IMatrix

Matrix-vector multiplication.

TWCNB - Enum constant in enum class smile.classification.DiscreteNaiveBayes.Model

Transformed Weight-normalized Complement Naive Bayes.

TWO_POINT - Enum constant in enum class smile.gap.Crossover

Two point crossover - two crossover point are selected, binary string from beginning of chromosome to the first crossover point is copied from one parent, the part from the first to the second crossover point is copied from the second parent and the rest is copied from the first parent.

type - Variable in class smile.data.type.StructField

Field data type.

type - Variable in class smile.timeseries.BoxTest

The type of test.

type() - Method in class smile.data.measure.CategoricalMeasure

Returns the data type that is suitable for this measure scale.

type() - Method in interface smile.data.vector.BaseVector

Returns the data type of elements.

type() - Method in interface smile.data.vector.BooleanVector

type() - Method in interface smile.data.vector.ByteVector

type() - Method in interface smile.data.vector.CharVector

type() - Method in interface smile.data.vector.DoubleVector

type() - Method in interface smile.data.vector.FloatVector

type() - Method in interface smile.data.vector.IntVector

type() - Method in interface smile.data.vector.LongVector

type() - Method in interface smile.data.vector.ShortVector

type() - Method in class smile.deep.tensor.Device

Returns the device type.

type(int) - Method in class smile.data.type.StructType

Returns the field data type.

type(String) - Method in class smile.plot.vega.FacetField

Sets the field's type of measurement.

type(String) - Method in class smile.plot.vega.Field

Sets the field's type of measurement.

type(String) - Method in class smile.plot.vega.Legend

Sets the type of the legend.

types() - Method in interface smile.data.DataFrame

Returns the column data types.

types() - Method in interface smile.data.Tuple

Returns the field data types.

types() - Method in class smile.data.type.StructType

Returns the field data types.

U

u - Variable in class smile.neighbor.lsh.PrH

The index of bucket.

U - Variable in class smile.math.matrix.BigMatrix.SVD

The left singular vectors U.

U - Variable in class smile.math.matrix.fp32.Matrix.SVD

The left singular vectors U.

U - Variable in class smile.math.matrix.Matrix.SVD

The left singular vectors U.

UH - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Interjection.

ulp(String) - Static method in interface smile.data.formula.Terms

The ulp(x) term.

ulp(Term) - Static method in interface smile.data.formula.Terms

The ulp(x) term.

UMAP - Class in smile.manifold

Uniform Manifold Approximation and Projection.

UMAP(int[], double[][], AdjacencyList) - Constructor for class smile.manifold.UMAP

Constructor.

umatrix() - Method in class smile.vq.SOM

Calculates the unified distance matrix (u-matrix) for visualization.

unboxed() - Method in interface smile.data.type.DataType

Returns the unboxed data type if this is a boxed primitive type.

unboxed() - Method in class smile.data.type.StructType

Updates the field type to the primitive one.

unescape(String) - Static method in interface smile.util.Strings

Unescapes a string that contains standard Java escape sequences.

UNIFORM - Enum constant in enum class smile.gap.Crossover

Uniform crossover - bits are randomly copied from the first or from the second parent.

union(DataFrame...) - Method in interface smile.data.DataFrame

Unions data frames vertically by rows.

union(DataFrame...) - Method in class smile.data.IndexDataFrame

unique() - Method in class smile.nlp.SimpleText

unique() - Method in interface smile.nlp.TextTerms

Returns the iterator of unique words.

unique(int[]) - Static method in class smile.math.MathEx

Find unique elements of vector.

unique(String[]) - Static method in class smile.math.MathEx

Find unique elements of vector.

UNIT - Enum constant in enum class smile.math.blas.Diag

Unit triangular.

unitize() - Method in interface smile.data.SparseDataset

Unitize each row so that L2 norm of x = 1.

unitize(double[]) - Static method in class smile.math.MathEx

Unitize an array so that L₂ norm of x = 1.

unitize1() - Method in interface smile.data.SparseDataset

Unitize each row so that L1 norm of x is 1.

unitize1(double[]) - Static method in class smile.math.MathEx

Unitize an array so that L₁ norm of x is 1.

unitize2(double[]) - Static method in class smile.math.MathEx

Unitize an array so that L₂ norm of x = 1.

UniversalGenerator - Class in smile.math.random

The so-called "Universal Generator" based on multiplicative congruential method, which originally appeared in "Toward a Universal Random Number Generator" by Marsaglia, Zaman and Tsang.

UniversalGenerator() - Constructor for class smile.math.random.UniversalGenerator

Initialize Random with default seed.

UniversalGenerator(int) - Constructor for class smile.math.random.UniversalGenerator

Initialize Random with a specified integer seed

UniversalGenerator(long) - Constructor for class smile.math.random.UniversalGenerator

Initialize Random with a specified long seed

unsqueeze(long) - Method in class smile.deep.tensor.Tensor

Returns a new tensor with a dimension of size one inserted at the specified position.

update(double) - Method in class smile.math.matrix.SparseMatrix.Entry

Update the entry value in the matrix.

update(double) - Method in class smile.util.SparseArray.Entry

Update the value of entry in the array.

update(double[]) - Method in class smile.feature.extraction.GHA

Update the model with a new sample.

update(double[]) - Method in class smile.vq.BIRCH

update(double[]) - Method in class smile.vq.GrowingNeuralGas

update(double[]) - Method in class smile.vq.NeuralGas

update(double[]) - Method in class smile.vq.NeuralMap

update(double[]) - Method in class smile.vq.SOM

update(double[]) - Method in interface smile.vq.VectorQuantizer

Update the codebook with a new observation.

update(double[][]) - Method in class smile.feature.extraction.GHA

Update the model with a set of samples.

update(double[][], double[]) - Method in class smile.regression.MLP

Updates the model with a mini-batch.

update(double[][], int[]) - Method in class smile.classification.MLP

Updates the model with a mini-batch.

update(double[], double) - Method in class smile.regression.LinearModel

Growing window recursive least squares with lambda = 1.

update(double[], double) - Method in class smile.regression.MLP

Updates the model with a single sample.

update(double[], double) - Method in class smile.vq.hebb.Neuron

Updates the reference vector by w += eps * (x - w).

update(double[], double, double) - Method in class smile.regression.LinearModel

Recursive least squares.

update(double[], int) - Method in class smile.classification.LogisticRegression.Binomial

update(double[], int) - Method in class smile.classification.LogisticRegression.Multinomial

update(double[], int) - Method in class smile.classification.MLP

Updates the model with a single sample.

update(double[], E) - Method in class smile.neighbor.MutableLSH

Update an entry with new key.

update(float) - Method in class smile.math.matrix.fp32.SparseMatrix.Entry

Update the entry value in the matrix.

update(int) - Method in class smile.base.mlp.MultilayerPerceptron

Updates the weights for mini-batch training.

update(int) - Method in class smile.manifold.TSNE

Performs additional iterations.

update(int[][], int) - Method in class smile.sequence.HMM

Updates the HMM by the Baum-Welch algorithm.

update(int[][], int[]) - Method in class smile.classification.DiscreteNaiveBayes

Batch learning of naive Bayes classifier on sequences, which are modeled as a bag of words.

update(int[], int) - Method in class smile.classification.DiscreteNaiveBayes

Online learning of naive Bayes classifier on a sequence, which is modeled as a bag of words.

update(int[], int) - Method in class smile.classification.Maxent.Binomial

update(int[], int) - Method in class smile.classification.Maxent.Multinomial

update(int, double) - Method in class smile.math.Complex.Array

Sets the i-th element with a real value.

update(int, double, double, double, double, double) - Method in class smile.base.mlp.InputLayer

update(int, double, double, double, double, double) - Method in class smile.base.mlp.Layer

Adjust network weights by back-propagation algorithm.

update(int, int, double) - Method in class smile.math.matrix.IMatrix

Sets A[i,j] = x for Scala users.

update(int, int, float) - Method in class smile.math.matrix.fp32.IMatrix

Sets A[i,j] = x for Scala users.

update(int, Complex) - Method in class smile.math.Complex.Array

Sets the i-th element.

update(String) - Method in class smile.data.SQL

Executes an INSERT, UPDATE, or DELETE statement.

update(Layer, int, int) - Method in class smile.base.mlp.optimizer.Adam

update(Layer, int, int) - Method in interface smile.base.mlp.optimizer.Optimizer

Updates a layer.

update(Layer, int, int) - Method in class smile.base.mlp.optimizer.RMSProp

update(Layer, int, int) - Method in class smile.base.mlp.optimizer.SGD

update(DataFrame) - Method in class smile.feature.extraction.GHA

Update the model with a new data frame.

update(DataFrame) - Method in class smile.regression.LinearModel

Online update the regression model with a new data frame.

update(Dataset<T, Double>) - Method in interface smile.regression.Regression

Updates the model with a mini-batch of new samples.

update(Dataset<T, Integer>) - Method in interface smile.classification.Classifier

Updates the model with a mini-batch of new samples.

update(Tuple) - Method in class smile.feature.extraction.GHA

Update the model with a new sample.

update(Tuple) - Method in class smile.regression.LinearModel

Online update the regression model with a new training instance.

update(Tensor, Tensor) - Method in class smile.deep.metric.Accuracy

update(Tensor, Tensor) - Method in interface smile.deep.metric.Metric

Updates the metric states with input data.

update(Tensor, Tensor) - Method in class smile.deep.metric.Precision

update(Tensor, Tensor) - Method in class smile.deep.metric.Recall

update(SparseArray[], int[]) - Method in class smile.classification.DiscreteNaiveBayes

Batch learning of naive Bayes classifier on sequences, which are modeled as a bag of words.

update(SparseArray, int) - Method in class smile.classification.DiscreteNaiveBayes

Online learning of naive Bayes classifier on a sequence, which is modeled as a bag of words.

update(SparseArray, int) - Method in class smile.classification.SparseLogisticRegression.Binomial

update(SparseArray, int) - Method in class smile.classification.SparseLogisticRegression.Multinomial

update(T[][], int) - Method in class smile.sequence.HMMLabeler

Updates the HMM by the Baum-Welch algorithm.

update(T[][], int, ToIntFunction<T>) - Method in class smile.sequence.HMM

Updates the HMM by the Baum-Welch algorithm.

update(T[], double[]) - Method in interface smile.regression.Regression

Updates the model with a mini-batch of new samples.

update(T[], int[]) - Method in interface smile.classification.Classifier

Updates the model with a mini-batch of new samples.

update(T, double) - Method in interface smile.regression.Regression

Online update the classifier with a new training instance.

update(T, int) - Method in interface smile.classification.Classifier

Online update the classifier with a new training instance.

UPGMALinkage - Class in smile.clustering.linkage

Unweighted Pair Group Method with Arithmetic mean (also known as average linkage).

UPGMALinkage(double[][]) - Constructor for class smile.clustering.linkage.UPGMALinkage

Constructor.

UPGMALinkage(int, float[]) - Constructor for class smile.clustering.linkage.UPGMALinkage

Constructor.

UPGMCLinkage - Class in smile.clustering.linkage

Unweighted Pair Group Method using Centroids (also known as centroid linkage).

UPGMCLinkage(double[][]) - Constructor for class smile.clustering.linkage.UPGMCLinkage

Constructor.

UPGMCLinkage(int, float[]) - Constructor for class smile.clustering.linkage.UPGMCLinkage

Constructor.

uplo() - Method in class smile.math.matrix.BandMatrix

Gets the format of packed matrix.

uplo() - Method in class smile.math.matrix.BigMatrix

Gets the format of packed matrix.

uplo() - Method in class smile.math.matrix.fp32.BandMatrix

Gets the format of packed matrix.

uplo() - Method in class smile.math.matrix.fp32.Matrix

Gets the format of packed matrix.

uplo() - Method in class smile.math.matrix.fp32.SymmMatrix

Gets the format of packed matrix.

uplo() - Method in class smile.math.matrix.Matrix

Gets the format of packed matrix.

uplo() - Method in class smile.math.matrix.SymmMatrix

Gets the format of packed matrix.

uplo(UPLO) - Method in class smile.math.matrix.BandMatrix

Sets the format of symmetric band matrix.

uplo(UPLO) - Method in class smile.math.matrix.BigMatrix

Sets the format of packed matrix.

uplo(UPLO) - Method in class smile.math.matrix.fp32.BandMatrix

Sets the format of symmetric band matrix.

uplo(UPLO) - Method in class smile.math.matrix.fp32.Matrix

Sets the format of packed matrix.

uplo(UPLO) - Method in class smile.math.matrix.Matrix

Sets the format of packed matrix.

UPLO - Enum Class in smile.math.blas

The format of packed matrix storage.

UPPER - Enum constant in enum class smile.math.blas.UPLO

Upper triangle is stored.

url(String) - Method in class smile.plot.vega.Data

Sets the url of the data source.

URL - Static variable in interface smile.util.Regex

Internet URLs.

usermeta(JsonNode) - Method in class smile.plot.vega.Concat

usermeta(JsonNode) - Method in class smile.plot.vega.Facet

usermeta(JsonNode) - Method in class smile.plot.vega.Repeat

usermeta(JsonNode) - Method in class smile.plot.vega.VegaLite

Optional metadata that will be passed to Vega.

usermeta(JsonNode) - Method in class smile.plot.vega.View

usermeta(Object) - Method in class smile.plot.vega.Concat

usermeta(Object) - Method in class smile.plot.vega.Facet

usermeta(Object) - Method in class smile.plot.vega.Repeat

usermeta(Object) - Method in class smile.plot.vega.VegaLite

Optional metadata that will be passed to Vega.

usermeta(Object) - Method in class smile.plot.vega.View

V

V - Variable in class smile.math.matrix.BigMatrix.SVD

The right singular vectors V.

V - Variable in class smile.math.matrix.fp32.Matrix.SVD

The right singular vectors V.

V - Variable in class smile.math.matrix.Matrix.SVD

The right singular vectors V.

v1 - Variable in class smile.graph.Graph.Edge

The id of one vertex connected by this edge.

v2 - Variable in class smile.graph.Graph.Edge

The id of the other vertex connected by this edge.

V2L() - Static method in class smile.vision.EfficientNet

EfficientNet-V2_L (largest) model.

V2L(String) - Static method in class smile.vision.EfficientNet

EfficientNet-V2_L (largest) model.

V2M() - Static method in class smile.vision.EfficientNet

EfficientNet-V2_M (larger) model.

V2M(String) - Static method in class smile.vision.EfficientNet

EfficientNet-V2_M (larger) model.

V2S() - Static method in class smile.vision.EfficientNet

EfficientNet-V2_S (baseline) model.

V2S(String) - Static method in class smile.vision.EfficientNet

EfficientNet-V2_S (baseline) model.

val(boolean) - Static method in interface smile.data.formula.Terms

Returns a constant boolean term.

val(byte) - Static method in interface smile.data.formula.Terms

Returns a constant byte term.

val(char) - Static method in interface smile.data.formula.Terms

Returns a constant char term.

val(double) - Static method in interface smile.data.formula.Terms

Returns a constant double precision floating number term.

val(float) - Static method in interface smile.data.formula.Terms

Returns a constant single precision floating number term.

val(int) - Static method in interface smile.data.formula.Terms

Returns a constant integer term.

val(long) - Static method in interface smile.data.formula.Terms

Returns a constant long integer term.

val(short) - Static method in interface smile.data.formula.Terms

Returns a constant short integer term.

val(Object) - Static method in interface smile.data.formula.Terms

Returns a constant object term.

valid(String) - Static method in class smile.plot.vega.Predicate

Test if a field is valid, meaning it is neither null nor NaN.

value - Variable in class smile.neighbor.Neighbor

The data object of neighbor.

value - Variable in class smile.util.MutableInt

The integer value.

value() - Method in enum class smile.deep.tensor.DeviceType

Returns the byte value of device type, which is compatible with PyTorch.

value(JsonNode) - Method in class smile.plot.vega.ImputeTransform

Sets the field value to use when the imputation method is "value".

VALUE - Enum constant in enum class smile.math.blas.EigenRange

All eigenvalues in the half-open interval (VL,VU] will be found.

valueOf(int) - Method in class smile.util.IntSet

Maps an index to the corresponding value.

valueOf(String) - Static method in enum class smile.base.cart.Loss.Type

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in interface smile.base.cart.Loss

Parses the loss.

valueOf(String) - Static method in enum class smile.base.cart.SplitRule

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.base.mlp.Cost

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.base.mlp.OutputFunction

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.classification.DiscreteNaiveBayes.Model

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.data.CategoricalEncoder

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.data.formula.DateFeature

Returns the enum constant of this class with the specified name.

valueOf(String) - Method in class smile.data.measure.CategoricalMeasure

valueOf(String) - Method in interface smile.data.measure.Measure

Returns a measurement value object represented by the argument string s.

valueOf(String) - Method in class smile.data.measure.NumericalMeasure

valueOf(String) - Method in class smile.data.type.ArrayType

valueOf(String) - Method in class smile.data.type.BooleanType

valueOf(String) - Method in class smile.data.type.ByteType

valueOf(String) - Method in class smile.data.type.CharType

valueOf(String) - Static method in enum class smile.data.type.DataType.ID

Returns the enum constant of this class with the specified name.

valueOf(String) - Method in interface smile.data.type.DataType

Returns the value from its string representation.

valueOf(String) - Method in class smile.data.type.DateTimeType

valueOf(String) - Method in class smile.data.type.DateType

valueOf(String) - Method in class smile.data.type.DecimalType

valueOf(String) - Method in class smile.data.type.DoubleType

valueOf(String) - Method in class smile.data.type.FloatType

valueOf(String) - Method in class smile.data.type.IntegerType

valueOf(String) - Method in class smile.data.type.LongType

valueOf(String) - Method in class smile.data.type.ObjectType

valueOf(String) - Method in class smile.data.type.ShortType

valueOf(String) - Method in class smile.data.type.StringType

valueOf(String) - Method in class smile.data.type.StructField

Returns the object value of string.

valueOf(String) - Method in class smile.data.type.StructType

valueOf(String) - Method in class smile.data.type.TimeType

valueOf(String) - Static method in enum class smile.deep.metric.Averaging

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.deep.tensor.DeviceType

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.deep.tensor.Layout

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.deep.tensor.ScalarType

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.feature.transform.Normalizer.Norm

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.gap.Crossover

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.io.JSON.Mode

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.blas.Diag

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.blas.EigenRange

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.blas.EVDJob

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.blas.Layout

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.blas.Side

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.blas.SVDJob

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.blas.Transpose

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.blas.UPLO

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.matrix.ARPACK.AsymmOption

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.matrix.ARPACK.SymmOption

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.matrix.fp32.ARPACK.AsymmOption

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.math.matrix.fp32.ARPACK.SymmOption

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.nlp.dictionary.EnglishDictionary

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.nlp.dictionary.EnglishStopWords

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.nlp.pos.PennTreebankPOS

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.plot.swing.Line.Style

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.timeseries.AR.Method

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.timeseries.BoxTest.Type

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.validation.metric.AdjustedMutualInformation.Method

Returns the enum constant of this class with the specified name.

valueOf(String) - Static method in enum class smile.validation.metric.NormalizedMutualInformation.Method

Returns the enum constant of this class with the specified name.

values - Variable in class smile.util.IntSet

Map of index to original values.

values() - Static method in enum class smile.base.cart.Loss.Type

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.base.cart.SplitRule

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.base.mlp.Cost

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.base.mlp.OutputFunction

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.classification.DiscreteNaiveBayes.Model

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.data.CategoricalEncoder

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.data.formula.DateFeature

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Method in class smile.data.measure.CategoricalMeasure

Returns the valid value set.

values() - Static method in enum class smile.data.type.DataType.ID

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.deep.metric.Averaging

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.deep.tensor.DeviceType

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.deep.tensor.Layout

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.deep.tensor.ScalarType

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.feature.transform.Normalizer.Norm

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.gap.Crossover

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.io.JSON.Mode

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.blas.Diag

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.blas.EigenRange

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.blas.EVDJob

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.blas.Layout

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.blas.Side

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.blas.SVDJob

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.blas.Transpose

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.blas.UPLO

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.matrix.ARPACK.AsymmOption

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.matrix.ARPACK.SymmOption

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.matrix.fp32.ARPACK.AsymmOption

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.math.matrix.fp32.ARPACK.SymmOption

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Method in class smile.neighbor.MutableLSH

Returns the values.

values() - Static method in enum class smile.nlp.dictionary.EnglishDictionary

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.nlp.dictionary.EnglishStopWords

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.nlp.pos.PennTreebankPOS

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.plot.swing.Line.Style

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.timeseries.AR.Method

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.timeseries.BoxTest.Type

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.validation.metric.AdjustedMutualInformation.Method

Returns an array containing the constants of this enum class, in the order they are declared.

values() - Static method in enum class smile.validation.metric.NormalizedMutualInformation.Method

Returns an array containing the constants of this enum class, in the order they are declared.

values(String) - Method in class smile.plot.vega.Data

Sets an array describing the data source.

values(String...) - Method in class smile.plot.vega.Legend

Sets the explicitly set the visible legend values.

values(List<T>) - Method in class smile.plot.vega.Data

Sets a list describing the data source.

values(T[]) - Method in class smile.plot.vega.Data

Sets an array describing the data source.

var - Variable in class smile.neighbor.lsh.NeighborHashValueModel

The variance of hash values of neighbors.

var(double[]) - Static method in class smile.math.MathEx

Returns the variance of an array.

var(float[]) - Static method in class smile.math.MathEx

Returns the variance of an array.

var(int[]) - Static method in class smile.math.MathEx

Returns the variance of an array.

variables() - Method in class smile.data.formula.AbstractBiFunction

variables() - Method in class smile.data.formula.AbstractFunction

variables() - Method in class smile.data.formula.Constant

variables() - Method in class smile.data.formula.Date

variables() - Method in class smile.data.formula.FactorCrossing

variables() - Method in class smile.data.formula.FactorInteraction

variables() - Method in interface smile.data.formula.Term

Returns the list of variables used in this term.

variance() - Method in class smile.feature.extraction.PCA

Returns the principal component variances, ordered from largest to smallest, which are the eigenvalues of the covariance or correlation matrix of learning data.

variance() - Method in class smile.feature.extraction.ProbabilisticPCA

Returns the variance of noise.

variance() - Method in class smile.stat.distribution.BernoulliDistribution

variance() - Method in class smile.stat.distribution.BetaDistribution

variance() - Method in class smile.stat.distribution.BinomialDistribution

variance() - Method in class smile.stat.distribution.ChiSquareDistribution

variance() - Method in class smile.stat.distribution.DiscreteMixture

variance() - Method in interface smile.stat.distribution.Distribution

Returns the variance of distribution.

variance() - Method in class smile.stat.distribution.EmpiricalDistribution

variance() - Method in class smile.stat.distribution.ExponentialDistribution

variance() - Method in class smile.stat.distribution.FDistribution

variance() - Method in class smile.stat.distribution.GammaDistribution

variance() - Method in class smile.stat.distribution.GaussianDistribution

variance() - Method in class smile.stat.distribution.GeometricDistribution

variance() - Method in class smile.stat.distribution.HyperGeometricDistribution

variance() - Method in class smile.stat.distribution.KernelDensity

variance() - Method in class smile.stat.distribution.LogisticDistribution

variance() - Method in class smile.stat.distribution.LogNormalDistribution

variance() - Method in class smile.stat.distribution.Mixture

variance() - Method in class smile.stat.distribution.NegativeBinomialDistribution

variance() - Method in class smile.stat.distribution.PoissonDistribution

variance() - Method in class smile.stat.distribution.ShiftedGeometricDistribution

variance() - Method in class smile.stat.distribution.TDistribution

variance() - Method in class smile.stat.distribution.WeibullDistribution

variance() - Method in class smile.timeseries.AR

Returns the residual variance.

variance() - Method in class smile.timeseries.ARMA

Returns the residual variance.

variance(double) - Method in interface smile.glm.model.Model

The variance function.

varianceProportion() - Method in class smile.feature.extraction.PCA

Returns the proportion of variance contained in each principal component, ordered from largest to smallest.

variances() - Method in class smile.manifold.KPCA

Returns the eigenvalues of kernel principal components, ordered from largest to smallest.

Variogram - Interface in smile.interpolation.variogram

In spatial statistics the theoretical variogram 2γ(x,y) is a function describing the degree of spatial dependence of a spatial random field or stochastic process Z(x).

VB - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Verb, base form.

VBD - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Verb, past tense.

VBG - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Verb, gerund or present participle.

VBN - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Verb, past participle.

VBP - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Verb, non-3rd person singular present.

VBZ - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Verb, 3rd person singular present.

vector(int) - Method in interface smile.data.DataFrame

Selects column based on the column index.

vector(int) - Method in class smile.data.IndexDataFrame

vector(Enum<?>) - Method in interface smile.data.DataFrame

Selects column using an enum value.

vector(String) - Method in interface smile.data.DataFrame

Selects column based on the column name.

Vector<T> - Interface in smile.data.vector

An immutable generic vector.

VectorQuantizer - Interface in smile.vq

Vector quantizer with competitive learning.

vectors - Variable in class smile.nlp.embedding.Word2Vec

The vector space.

vectors() - Method in class smile.base.svm.KernelMachine

Returns the support vectors of kernel machines.

VECTORS - Enum constant in enum class smile.math.blas.EVDJob

Both eigen values and vectors are computed.

VegaLite - Class in smile.plot.vega

Vega-Lite specifications are JSON objects that describe a diverse range of interactive visualizations.

VegaLite() - Constructor for class smile.plot.vega.VegaLite

Constructor.

vertical(VegaLite...) - Static method in class smile.plot.vega.Concat

Returns a vertical concatenation of views.

View - Class in smile.plot.vega

Single view specification, which describes a view that uses a single mark type to visualize the data.

View() - Constructor for class smile.plot.vega.View

Constructor.

View(String) - Constructor for class smile.plot.vega.View

Constructor.

ViewComposition - Interface in smile.plot.vega

All view composition specifications (layer, facet, concat, and repeat) can have the resolve property for scale, axes, and legend resolution.

viewConfig() - Method in class smile.plot.vega.VegaLite

Returns the configuration object defining the style of a single view visualization.

ViewConfig - Class in smile.plot.vega

The style of a single view visualization.

ViewLayoutComposition - Interface in smile.plot.vega

All view layout composition (facet, concat, and repeat) can have the following layout properties: align, bounds, center, spacing.

VIOLET_RED - Static variable in interface smile.plot.swing.Palette

VisionModel - Class in smile.vision

The computer vision models.

VisionModel(LayerBlock, Transform) - Constructor for class smile.vision.VisionModel

Constructor.

visit(int) - Method in interface smile.graph.Visitor

Performs some operations on the currently-visiting vertex during DFS or BFS.

Visitor - Interface in smile.graph

A visitor is encapsulation of some operation on graph vertices during traveling graph (DFS or BFS).

viterbi(Tuple[]) - Method in class smile.sequence.CRF

Labels sequence with Viterbi algorithm.

viterbi(T[]) - Method in class smile.sequence.CRFLabeler

Labels sequence with Viterbi algorithm.

Vl - Variable in class smile.math.matrix.BigMatrix.EVD

The left eigenvectors.

Vl - Variable in class smile.math.matrix.fp32.Matrix.EVD

The left eigenvectors.

Vl - Variable in class smile.math.matrix.Matrix.EVD

The left eigenvectors.

vote(Tuple, double[]) - Method in class smile.classification.RandomForest

Predict and estimate the probability by voting.

Vr - Variable in class smile.math.matrix.BigMatrix.EVD

The right eigenvectors.

Vr - Variable in class smile.math.matrix.fp32.Matrix.EVD

The right eigenvectors.

Vr - Variable in class smile.math.matrix.Matrix.EVD

The right eigenvectors.

W

w - Variable in class smile.neighbor.LSH

The width of projection.

w - Variable in class smile.regression.GaussianProcessRegression

The linear weights.

w - Variable in class smile.vq.hebb.Neuron

The reference vector.

w1 - Variable in class smile.nlp.Bigram

Immutable first word of bigram.

w2 - Variable in class smile.nlp.Bigram

Immutable second word of bigram.

walkin(File, List<File>) - Static method in class smile.nlp.pos.HMMPOSTagger

Recursive function to descend into the directory tree and find all the files that end with ".POS"

WardLinkage - Class in smile.clustering.linkage

Ward's linkage.

WardLinkage(double[][]) - Constructor for class smile.clustering.linkage.WardLinkage

Constructor.

WardLinkage(int, float[]) - Constructor for class smile.clustering.linkage.WardLinkage

Constructor.

Wavelet - Class in smile.wavelet

A wavelet is a wave-like oscillation with an amplitude that starts out at zero, increases, and then decreases back to zero.

Wavelet(double[]) - Constructor for class smile.wavelet.Wavelet

Constructor.

WaveletShrinkage - Interface in smile.wavelet

The wavelet shrinkage is a signal denoising technique based on the idea of thresholding the wavelet coefficients.

WCNB - Enum constant in enum class smile.classification.DiscreteNaiveBayes.Model

Weight-normalized Complement Naive Bayes.

WDT - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Wh-determiner.

WEEK_OF_MONTH - Enum constant in enum class smile.data.formula.DateFeature

The count of weeks within the month.

WEEK_OF_YEAR - Enum constant in enum class smile.data.formula.DateFeature

The count of weeks within the year.

WeibullDistribution - Class in smile.stat.distribution

The Weibull distribution is one of the most widely used lifetime distributions in reliability engineering.

WeibullDistribution(double) - Constructor for class smile.stat.distribution.WeibullDistribution

Constructor.

WeibullDistribution(double, double) - Constructor for class smile.stat.distribution.WeibullDistribution

Constructor.

weight - Variable in class smile.base.mlp.Layer

The affine transformation matrix.

weight - Variable in class smile.classification.RandomForest.Model

The weight of tree, which can be used when aggregating tree votes.

weight - Variable in class smile.graph.Graph.Edge

The weight of edge.

Weighted - Enum constant in enum class smile.deep.metric.Averaging

Weighted macro for imbalanced classes.

weightGradient - Variable in class smile.base.mlp.Layer

The weight gradient.

weightGradientMoment1 - Variable in class smile.base.mlp.Layer

The first moment of weight gradient.

weightGradientMoment2 - Variable in class smile.base.mlp.Layer

The second moment of weight gradient.

weights() - Method in class smile.base.svm.KernelMachine

Returns the weights of instances.

weightUpdate - Variable in class smile.base.mlp.Layer

The weight update.

where(Tensor, double, double) - Method in class smile.deep.tensor.Tensor

Returns a tensor of elements selected from either input or other, depending on condition.

where(Tensor, int, int) - Method in class smile.deep.tensor.Tensor

Returns a tensor of elements selected from either input or other, depending on condition.

whichMax(double[]) - Static method in class smile.math.MathEx

Returns the index of maximum value of an array.

whichMax(double[][]) - Static method in class smile.math.MathEx

Returns the index of maximum value of a matrix.

whichMax(float[]) - Static method in class smile.math.MathEx

Returns the index of maximum value of an array.

whichMax(int[]) - Static method in class smile.math.MathEx

Returns the index of maximum value of an array.

whichMin(double[]) - Static method in class smile.math.MathEx

Returns the index of minimum value of an array.

whichMin(double[][]) - Static method in class smile.math.MathEx

Returns the index of minimum value of an matrix.

whichMin(float[]) - Static method in class smile.math.MathEx

Returns the index of minimum value of an array.

whichMin(int[]) - Static method in class smile.math.MathEx

Returns the index of minimum value of an array.

WHITE - Static variable in interface smile.plot.swing.Palette

wi - Variable in class smile.math.matrix.BigMatrix.EVD

The imaginary part of eigenvalues.

wi - Variable in class smile.math.matrix.fp32.Matrix.EVD

The imaginary part of eigenvalues.

wi - Variable in class smile.math.matrix.Matrix.EVD

The imaginary part of eigenvalues.

width - Variable in class smile.manifold.LaplacianEigenmap

The width of heat kernel.

width(double) - Method in class smile.plot.vega.Mark

Sets the width of the marks.

width(int) - Method in class smile.plot.vega.Layer

width(int) - Method in class smile.plot.vega.View

Sets the width of a plot with a continuous x-field, or the fixed width of a plot a discrete x-field or no x-field.

width(String) - Method in class smile.plot.vega.Layer

width(String) - Method in class smile.plot.vega.View

To enable responsive sizing on width.

widthStep(int) - Method in class smile.plot.vega.Layer

widthStep(int) - Method in class smile.plot.vega.View

For a discrete x-field, sets the width per discrete step.

window() - Method in class smile.plot.swing.Canvas

Shows the plot in a window.

window() - Method in class smile.plot.swing.PlotGrid

Shows the plot group in a window.

window() - Method in class smile.plot.swing.PlotPanel

Shows the plot in a window.

window(WindowTransformField...) - Method in class smile.plot.vega.Transform

Creates a data specification object.

WindowTransform - Class in smile.plot.vega

The window transform performs calculations over sorted groups of data objects.

WindowTransformField - Record Class in smile.plot.vega

A sort field definition for sorting data objects within a window.

WindowTransformField(String, String, double, String) - Constructor for record class smile.plot.vega.WindowTransformField

Creates an instance of a WindowTransformField record class.

winsor(double[]) - Static method in class smile.math.Scaler

Returns the scaler that map the values into the range [0, 1].

winsor(double[], double, double) - Static method in class smile.math.Scaler

Returns the scaler that map the values into the range [0, 1].

WinsorScaler - Class in smile.feature.transform

Scales all numeric variables into the range [0, 1].

WinsorScaler() - Constructor for class smile.feature.transform.WinsorScaler

Wireframe - Class in smile.plot.swing

A wire frame model specifies each edge of the physical object where two mathematically continuous smooth surfaces meet, or by connecting an object's constituent vertices using straight lines or curves.

Wireframe(double[][], int[][], Color) - Constructor for class smile.plot.swing.Wireframe

Constructor.

woe - Variable in class smile.feature.selection.InformationValue

Weight of evidence.

Word2Vec - Class in smile.nlp.embedding

Word2vec is a group of related models that are used to produce word embeddings.

Word2Vec(String[], float[][]) - Constructor for class smile.nlp.embedding.Word2Vec

Constructor.

words - Variable in class smile.nlp.embedding.Word2Vec

The vocabulary.

words - Variable in class smile.nlp.NGram

Immutable word sequences.

words() - Method in class smile.nlp.SimpleText

words() - Method in interface smile.nlp.TextTerms

Returns the iterator of the words of the document.

WP - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Wh-pronoun.

WP$ - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Possessive wh-pronoun.

WPGMALinkage - Class in smile.clustering.linkage

Weighted Pair Group Method with Arithmetic mean.

WPGMALinkage(double[][]) - Constructor for class smile.clustering.linkage.WPGMALinkage

Constructor.

WPGMALinkage(int, float[]) - Constructor for class smile.clustering.linkage.WPGMALinkage

Constructor.

WPGMCLinkage - Class in smile.clustering.linkage

Weighted Pair Group Method using Centroids (also known as median linkage).

WPGMCLinkage(double[][]) - Constructor for class smile.clustering.linkage.WPGMCLinkage

Constructor.

WPGMCLinkage(int, float[]) - Constructor for class smile.clustering.linkage.WPGMCLinkage

Constructor.

wr - Variable in class smile.math.matrix.BigMatrix.EVD

The real part of eigenvalues.

wr - Variable in class smile.math.matrix.fp32.Matrix.EVD

The real part of eigenvalues.

wr - Variable in class smile.math.matrix.Matrix.EVD

The real part of eigenvalues.

WRB - Enum constant in enum class smile.nlp.pos.PennTreebankPOS

Wh-adverb.

write(DataFrame, Path) - Method in class smile.io.Arrow

Writes the data frame to an arrow file.

write(DataFrame, Path) - Method in class smile.io.CSV

Writes the data frame to a csv file with UTF-8 encoding.

write(DataFrame, Path, String) - Static method in class smile.io.Arff

Writes the data frame to an ARFF file.

Write - Interface in smile.io

Writes data to external storage systems.

X

x - Variable in class smile.base.cart.CART

The training data.

x - Variable in class smile.math.matrix.fp32.SparseMatrix.Entry

The value.

x - Variable in class smile.math.matrix.SparseMatrix.Entry

The value.

x - Variable in class smile.regression.GaussianProcessRegression.JointPrediction

The query points where the GP is evaluated.

x - Variable in class smile.util.SparseArray.Entry

The value of entry.

x() - Method in record class smile.data.SampleInstance

Returns the value of the x record component.

x() - Method in class smile.timeseries.AR

Returns the time series.

x() - Method in class smile.timeseries.ARMA

Returns the time series.

x(double) - Method in class smile.plot.vega.Legend

Sets the custom x-position for legend with orient "none".

x(double) - Method in class smile.plot.vega.Mark

Sets the X coordinates of the marks.

x(String) - Method in class smile.plot.vega.Mark

Sets the width of horizontal "bar" and "area" without specified x2 or width.

x(DataFrame) - Method in class smile.data.formula.Formula

Returns a data frame of predictors.

x(Tuple) - Method in class smile.data.formula.Formula

Apply the formula on a tuple to generate the predictors data.

x2(double) - Method in class smile.plot.vega.Mark

Sets the X2 coordinates for ranged "area", "bar", "rect", and "rule".

x2(String) - Method in class smile.plot.vega.Mark

Sets the width.

x2Offset(double) - Method in class smile.plot.vega.Mark

Sets the offset for x2-position.

xAx(double[]) - Method in class smile.math.matrix.BigMatrix

Returns the quadratic form x' * A * x.

xAx(double[]) - Method in class smile.math.matrix.Matrix

Returns the quadratic form x' * A * x.

xAx(float[]) - Method in class smile.math.matrix.fp32.Matrix

Returns the quadratic form x' * A * x.

XMeans - Class in smile.clustering

X-Means clustering algorithm, an extended K-Means which tries to automatically determine the number of clusters based on BIC scores.

XMeans(double, double[][], int[]) - Constructor for class smile.clustering.XMeans

Constructor.

xOffset(double) - Method in class smile.plot.vega.Mark

Sets the offset for x-position.

Y

y - Variable in class smile.classification.ClassLabels

The sample class id in [0, k).

y - Variable in class smile.clustering.PartitionClustering

The cluster labels of data.

y() - Method in record class smile.data.SampleInstance

Returns the value of the y record component.

y(double) - Method in class smile.plot.vega.Legend

Sets the custom y-position for legend with orient "none".

y(double) - Method in class smile.plot.vega.Mark

Sets the Y coordinates of the marks.

y(String) - Method in class smile.plot.vega.Mark

Sets the height of horizontal "bar" and "area" without specified x2 or width.

y(DataFrame) - Method in class smile.data.formula.Formula

Returns the response vector.

y(Tuple) - Method in class smile.data.formula.Formula

Returns the real-valued response value.

y2(double) - Method in class smile.plot.vega.Mark

Sets the Y2 coordinates for ranged "area", "bar", "rect", and "rule".

y2(String) - Method in class smile.plot.vega.Mark

Sets the width.

y2Offset(double) - Method in class smile.plot.vega.Mark

Sets the offset for y2-position.

YEAR - Enum constant in enum class smile.data.formula.DateFeature

The year represented by an integer.

YELLOW - Static variable in interface smile.plot.swing.Palette

yint(Tuple) - Method in class smile.data.formula.Formula

Returns the integer-valued response value.

yOffset(double) - Method in class smile.plot.vega.Mark

Sets the offset for y-position.

YuleWalker - Enum constant in enum class smile.timeseries.AR.Method

Yule-Walker method.

YYYYMMDD - Static variable in class smile.swing.table.DateCellEditor

YYYYMMDD - Static variable in class smile.swing.table.DateCellRenderer

YYYYMMDD_HHMM - Static variable in class smile.swing.table.DateCellEditor

YYYYMMDD_HHMM - Static variable in class smile.swing.table.DateCellRenderer

YYYYMMDD_HHMMSS - Static variable in class smile.swing.table.DateCellEditor

YYYYMMDD_HHMMSS - Static variable in class smile.swing.table.DateCellRenderer

Z

zero(boolean) - Method in class smile.plot.vega.Field

If true, ensures that a zero baseline value is included in the scale domain.

zeros(long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor filled with all zeros.

zeros(Tensor.Options, long...) - Static method in class smile.deep.tensor.Tensor

Returns a tensor filled with all zeros.

zindex(int) - Method in class smile.plot.vega.Axis

Sets a non-negative integer indicating the z-index of the axis.

zindex(int) - Method in class smile.plot.vega.Legend

Sets a non-negative integer indicating the z-index of the legend.

zipWithIndex(double[]) - Static method in class smile.plot.swing.Line

Returns a 2-dimensional array with the index as the x coordinate.

zoom(boolean) - Method in class smile.plot.swing.PlotPanel

Zooms in/out the plot.

ztest - Variable in class smile.glm.GLM

The coefficients, their standard errors, z-scores, and p-values.

ztest() - Method in class smile.glm.GLM

Returns the z-test of the coefficients (including intercept).

_

_1() - Method in record class smile.util.IntPair

Returns the value of the _1 record component.

_1() - Method in record class smile.util.Tuple2

Returns the value of the _1 record component.

_2() - Method in record class smile.util.IntPair

Returns the value of the _2 record component.

_2() - Method in record class smile.util.Tuple2

Returns the value of the _2 record component.

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