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() - Method in record class smile.validation.ClassificationMetrics

Returns the value of the accuracy record component.

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.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

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(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(T) - Method in class smile.util.AutoScope

Adds resource to this scope.

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

Tests if all elements in the tensor are true.

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.

alpha() - Method in record class smile.swing.AlphaIcon

Returns the value of the alpha record component.

AlphaIcon - Record Class in smile.swing

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

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

Creates an instance of a AlphaIcon record class.

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() - Method in record class smile.association.AssociationRule

Returns the value of the antecedent record component.

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.stemmer.Stemmer

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

Creates and attaches a copy-paste adapter for a table.

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(Tensor, Tensor, Tensor) - Static method in interface smile.llm.RotaryPositionalEncoding

Applies rotary embeddings to the input query and key tensors.

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 a boolean-valued result.

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

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

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

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

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

applyAsDouble(double[], double[]) - Method in interface smile.validation.metric.RegressionMetric

applyAsDouble(int[], int[]) - Method in interface smile.validation.metric.ClassificationMetric

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

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

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

Applies the term on a data object and produces a 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(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.

assistant - Enum constant in enum class smile.llm.Role

AI assistant.

AssociationRule - Record Class in smile.association

Association rule object.

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

Creates an instance of a AssociationRule record class.

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.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.LinearLayer

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

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

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 enum class smile.deep.tensor.ScalarType

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.

Attention - Class in smile.llm.llama

Multi-head attention.

Attention(ModelArgs) - Constructor for class smile.llm.llama.Attention

Constructor.

attractors - Variable in class smile.clustering.DENCLUE

The density attractor of each observation.

auc() - Method in record class smile.validation.ClassificationMetrics

Returns the value of the auc record component.

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.

Averaging - Enum Class in smile.validation.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 - Record Class in smile.validation

A bag of random selected samples.

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

Creates an instance of a Bag record class.

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's 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 a Bernoulli from the given samples.

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

Constructor.

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.

bias() - Method in record class smile.data.formula.Intercept

Returns the value of the bias record component.

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.Delete

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

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

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 record class smile.data.formula.Intercept

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.Round

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

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

Binds the term to a schema.

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

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:

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.

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

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

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() - Method in record class smile.feature.selection.InformationValue

Returns the value of the breaks record component.

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

build(String, String, int, int) - Static method in class smile.llm.llama.Llama

Builds a Llama instance by initializing and loading a model checkpoint.

build(String, String, int, int, Integer) - Static method in class smile.llm.llama.Llama

Builds a Llama instance by initializing and loading a model checkpoint.

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.

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

Returns the byte array of tensor elements

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 - Variable in class smile.plot.swing.Projection

The canvas associated with this projection.

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.

chat(Message[][], int, double, double, boolean, Long, SubmissionPublisher<String>) - Method in class smile.llm.llama.Llama

Generates assistant responses for a list of conversational dialogs.

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() - Method in record class smile.stat.hypothesis.ChiSqTest

Returns the value of the chisq record component.

ChiSqTest - Record 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 record class smile.stat.hypothesis.ChiSqTest

Constructor.

ChiSqTest(String, double, double, double, double) - Constructor for record class smile.stat.hypothesis.ChiSqTest

Creates an instance of a ChiSqTest record class.

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<T> - 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 - Record Class in smile.validation

The classification validation metrics.

ClassificationMetrics(double, double, int, int, double) - Constructor for record class smile.validation.ClassificationMetrics

Constructor.

ClassificationMetrics(double, double, int, int, double, double) - Constructor for record class smile.validation.ClassificationMetrics

Constructor of multiclass soft classifier validation.

ClassificationMetrics(double, double, int, int, double, double, double, double, double, double) - Constructor for record class smile.validation.ClassificationMetrics

Constructor of binary classifier validation.

ClassificationMetrics(double, double, int, int, double, double, double, double, double, double, double, double) - Constructor for record 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 record class smile.validation.ClassificationMetrics

Creates an instance of a ClassificationMetrics record class.

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(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.math.matrix.BigMatrix

close() - Method in class smile.util.AutoScope

close() - Method in class smile.vision.ImageDataset

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 record class smile.feature.selection.InformationValue

compareTo(SignalNoiseRatio) - Method in record class smile.feature.selection.SignalNoiseRatio

compareTo(SumSquaresRatio) - Method in record class smile.feature.selection.SumSquaresRatio

compareTo(Chromosome) - Method in class smile.gap.BitString

compareTo(PrH) - Method in record class smile.neighbor.lsh.PrH

compareTo(Probe) - Method in class smile.neighbor.lsh.Probe

compareTo(PrZ) - Method in record 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

complete(String[], int, double, double, boolean, Long, SubmissionPublisher<String>) - Method in class smile.llm.llama.Llama

Performs text completion for a list of prompts

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.

CompletionPrediction - Record Class in smile.llm

Prompt completion prediction.

CompletionPrediction(String, String, int[], int[], FinishReason, float[]) - Constructor for record class smile.llm.CompletionPrediction

Creates an instance of a CompletionPrediction record class.

completionTokens() - Method in record class smile.llm.CompletionPrediction

Returns the value of the completionTokens record component.

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 record class smile.stat.distribution.DiscreteMixture.Component

Creates an instance of a Component record class.

Component(double, Distribution) - Constructor for record class smile.stat.distribution.Mixture.Component

Creates an instance of a Component record class.

Component(double, MultivariateDistribution) - Constructor for record class smile.stat.distribution.MultivariateMixture.Component

Creates an instance of a Component record class.

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

computeFreqCis(int, int) - Static method in interface smile.llm.RotaryPositionalEncoding

Precompute the frequency tensor for complex exponentials (cis).

computeFreqCis(int, int, double, boolean) - Static method in interface smile.llm.RotaryPositionalEncoding

Precompute the frequency tensor for complex exponentials (cis).

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() - Method in record class smile.association.AssociationRule

Returns the value of the confidence record component.

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 - Record Class in smile.validation.metric

The confusion matrix of truth and predictions.

ConfusionMatrix(int[][]) - Constructor for record class smile.validation.metric.ConfusionMatrix

Creates an instance of a ConfusionMatrix record class.

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() - Method in record class smile.association.AssociationRule

Returns the value of the consequent record component.

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

content() - Method in record class smile.llm.CompletionPrediction

Returns the value of the content record component.

content() - Method in record class smile.llm.Message

Returns the value of the content record component.

content_filter - Enum constant in enum class smile.llm.FinishReason

Omitted content due to a flag from content filters.

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

Returns a contiguous in memory tensor containing the same data as this tensor.

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() - Method in class smile.math.matrix.BandMatrix

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

copy() - Method in class smile.math.matrix.fp32.BandMatrix

copy() - Method in class smile.math.matrix.fp32.IMatrix

Returns a deep copy of matrix.

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

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

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

copy() - Method in class smile.math.matrix.IMatrix

Returns a deep copy of matrix.

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

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

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

copy() - Method in class smile.neighbor.lsh.Probe

Returns a shallow copy that shares the range array.

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() - Method in record class smile.stat.hypothesis.CorTest

Returns the value of the cor record component.

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 - Record Class in smile.stat.hypothesis

Correlation test.

CorTest(String, double, double, double, double) - Constructor for record class smile.stat.hypothesis.CorTest

Creates an instance of a CorTest record class.

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 sample size 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() - Method in record class smile.stat.hypothesis.ChiSqTest

Returns the value of the CramerV record component.

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() - Method in record class smile.validation.ClassificationMetrics

Returns the value of the crossentropy record component.

crossEntropy() - Static method in interface smile.deep.Loss

Cross Entropy Loss Function.

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

Computes the cross entropy loss between input logits and target.

CrossEntropy - Interface in smile.validation.metric

Cross entropy generalizes the log loss metric to multiclass problems.

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

crossover(T) - 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.vq.BIRCH

The dimensionality of data.

d() - Method in record class smile.stat.hypothesis.KSTest

Returns the value of the d record component.

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.

Delete - Class in smile.data.formula

Remove a factor from the formula.

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

Constructor.

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.

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 - Variable in class smile.deep.layer.LayerBlock

The compute device.

device() - Static method in interface smile.deep.CUDA

Returns the default CUDA device.

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

Returns the compute device of module.

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.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 record class smile.stat.hypothesis.ChiSqTest

Returns the value of the df record component.

df() - Method in record class smile.stat.hypothesis.CorTest

Returns the value of the df record component.

df() - Method in record class smile.stat.hypothesis.TTest

Returns the value of the df record component.

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() - Method in record class smile.stat.hypothesis.FTest

Returns the value of the df1 record component.

df2() - Method in record class smile.stat.hypothesis.FTest

Returns the value of the df2 record component.

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.

dim() - Method in record class smile.llm.llama.ModelArgs

Returns the value of the dim record component.

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.

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 - Record 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() - Method in record class smile.stat.distribution.DiscreteMixture.Component

Returns the value of the distribution record component.

distribution() - Method in record class smile.stat.distribution.Mixture.Component

Returns the value of the distribution record component.

distribution() - Method in record class smile.stat.distribution.MultivariateMixture.Component

Returns the value of the distribution record 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.

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 - Class in smile.data.formula

The special term "." means all columns not otherwise in the formula in the context of a data frame.

Dot() - Constructor for class smile.data.formula.Dot

Constructor.

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.

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

Returns the double array of tensor elements

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(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 - Variable in class smile.deep.layer.LayerBlock

The data type.

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

Returns the compute device of module.

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

Returns the data type.

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.

encodeDialog(Message...) - Method in class smile.llm.llama.Tokenizer

Encodes the messages of a dialog.

encodeMessage(Message) - Method in class smile.llm.llama.Tokenizer

Encodes a message.

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's 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's 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's entropy.

entropy() - Method in class smile.stat.distribution.HyperGeometricDistribution

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

Shannon's 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's entropy.

entropy() - Method in interface smile.stat.distribution.MultivariateDistribution

Shannon's 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's 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 record class smile.association.AssociationRule

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.association.ItemSet

Indicates whether some other object is "equal to" this one.

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 record class smile.data.formula.Intercept

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.data.formula.Variable

Indicates whether some other object is "equal to" this one.

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.feature.selection.InformationValue

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.feature.selection.SignalNoiseRatio

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.feature.selection.SumSquaresRatio

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.llm.CompletionPrediction

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.llm.llama.ModelArgs

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.llm.Message

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 record class smile.neighbor.lsh.PrH

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.neighbor.lsh.PrZ

Indicates whether some other object is "equal to" this one.

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.stat.distribution.DiscreteMixture.Component

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.stat.distribution.Mixture.Component

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.stat.distribution.MultivariateMixture.Component

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.stat.hypothesis.ChiSqTest

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.stat.hypothesis.CorTest

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.stat.hypothesis.FTest

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.stat.hypothesis.KSTest

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.stat.hypothesis.TTest

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.swing.AlphaIcon

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.validation.Bag

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.validation.ClassificationMetrics

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.validation.metric.ConfusionMatrix

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in record class smile.validation.RegressionMetrics

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() - Method in class smile.regression.LinearModel

Returns the residual standard error.

error() - Method in record class smile.validation.ClassificationMetrics

Returns the value of the error record component.

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.layer.LayerBlock

Sets the layer block in the evaluation/inference mode.

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.Delete

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

Returns a new view of this tensor with singleton dimensions expanded to a larger size.

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() - Method in record class smile.stat.hypothesis.FTest

Returns the value of the f record component.

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.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() - Method in record class smile.validation.ClassificationMetrics

Returns the value of the f1 record component.

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.

family() - Method in class smile.llm.llama.Llama

Returns the model family name.

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

Returns the split feature.

feature() - Method in record class smile.feature.selection.InformationValue

Returns the value of the feature record component.

feature() - Method in record class smile.feature.selection.SignalNoiseRatio

Returns the value of the feature record component.

feature() - Method in record class smile.feature.selection.SumSquaresRatio

Returns the value of the feature record component.

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.

FeedForward - Class in smile.llm.llama

Feedforward layer in Transformer.

FeedForward(int, int, int, Double) - Constructor for class smile.llm.llama.FeedForward

Constructor.

ffnDimMultiplier() - Method in record class smile.llm.llama.ModelArgs

Returns the value of the ffnDimMultiplier record component.

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 metadata 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.

fillna(double) - Method in interface smile.data.DataFrame

Fills NaN/Inf values of floating number columns using the specified value.

fillna(double) - Method in interface smile.data.vector.DoubleVector

Fills NaN/Inf values using the specified value.

fillna(double) - Method in interface smile.data.vector.NumberVector

Fill null/NaN/Inf values using the specified value.

fillna(float) - Method in interface smile.data.vector.FloatVector

Fills NaN/Inf values using the specified value.

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.

FinishReason - Enum Class in smile.llm

The reasons that the chat completions finish.

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 an 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 an 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 record class smile.feature.selection.InformationValue

Calculates the information value.

fit(DataFrame, String) - Static method in record class smile.feature.selection.SignalNoiseRatio

Calculates the signal noise ratio of numeric variables.

fit(DataFrame, String) - Static method in record 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 record 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 hyperparameters.

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 hyperparameters.

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 a 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 hyperparameters.

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 an RBF network.

fit(T[], double[], RBF<T>[], boolean) - Static method in class smile.regression.RBFNetwork

Fits an 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 hyperparameters.

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 an RBF network.

fit(T[], int[], RBF<T>[], boolean) - Static method in class smile.classification.RBFNetwork

Fits an 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 a one-class SVM.

fit(T[], MercerKernel<T>, double, double) - Static method in class smile.anomaly.SVM

Fits a 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() - Method in record class smile.validation.ClassificationMetrics

Returns the value of the fitTime record component.

fitTime() - Method in record class smile.validation.RegressionMetrics

Returns the value of the fitTime record component.

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.

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

Returns the float array of tensor elements

FloatArrayCellRenderer - Class in smile.swing.table

Float array renderer in JTable.

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

Constructor.

FloatArrayFormatter - Class in smile.swing.text

Text formatter for floating array values.

FloatArrayFormatter() - Constructor for class smile.swing.text.FloatArrayFormatter

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.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.LinearLayer

forward(Tensor) - Method in class smile.deep.layer.MaxPool2dLayer

forward(Tensor) - Method in class smile.deep.layer.RMSNormLayer

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.llama.FeedForward

Feed forward.

forward(Tensor) - Method in class smile.llm.llama.Transformer

forward(Tensor) - Method in class smile.llm.PositionalEncoding

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

forward(Tensor, int) - Method in class smile.llm.llama.Transformer

Forward pass through the model.

forward(Tensor, int, Tensor, Tensor) - Method in class smile.llm.llama.Attention

Forward pass through the attention module.

forward(Tensor, int, Tensor, Tensor) - Method in class smile.llm.llama.TransformerBlock

Forward pass through the block.

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(String, int, int) - Static method in record class smile.llm.llama.ModelArgs

Loads the model hyperparameters from a JSON file.

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, Averaging) - 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 - Record 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 record class smile.stat.hypothesis.FTest

Creates an instance of a FTest record class.

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

Returns a tensor filled with the given value.

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

Returns a tensor filled with the given value.

Function - Interface in smile.math

An interface representing a univariate real function.

function_call - Enum constant in enum class smile.llm.FinishReason

The model decided to call a 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.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

generate(int[][], int, double, double, boolean, Long, SubmissionPublisher<String>) - Method in class smile.llm.llama.Llama

Generates text sequences based on provided prompts.

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.

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(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 record class smile.swing.AlphaIcon

Gets the height of the bounding rectangle of this AlphaIcon.

getIconWidth() - Method in record 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.

getNumThreads() - Static method in class smile.deep.tensor.Device

Returns the number of threads used for intraop parallelism on CPU.

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 subclass should implement this method to return the real number of rows in the model.

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

Returns true if autograd should record operations on this tensor.

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 toolbar to control the plot.

getToolbar() - Method in class smile.swing.table.PageTableModel

Returns a toolbar 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 C