Index

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All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

$

$ - Enum constant in enum class smile.nlp.pos.PennTreebankPOS
Punctuation $
$(String) - Static method in interface smile.data.formula.Terms
Creates a variable.

A

a - Variable in class smile.validation.metric.ContingencyTable
The row sum of contingency table.
aat() - Method in class smile.math.matrix.BigMatrix
Returns A * A'.
aat() - Method in class smile.math.matrix.fp32.Matrix
Returns A * A'.
aat() - Method in class smile.math.matrix.fp32.SparseMatrix
Returns A * A'.
aat() - Method in class smile.math.matrix.Matrix
Returns A * A'.
aat() - Method in class smile.math.matrix.SparseMatrix
Returns A * A'.
Abbreviations - Interface in smile.nlp.dictionary
A dictionary interface for abbreviations.
abs() - Method in class smile.math.Complex
Returns the abs/modulus/magnitude.
abs(String) - Static method in interface smile.data.formula.Terms
The abs(x) term.
abs(Term) - Static method in interface smile.data.formula.Terms
The abs(x) term.
Abs - Class in smile.data.formula
The term of abs function.
Abs(Term) - Constructor for class smile.data.formula.Abs
Constructor.
AbstractBiFunction - Class in smile.data.formula
This class provides a skeletal implementation of the bi-function term.
AbstractBiFunction(String, Term, Term) - Constructor for class smile.data.formula.AbstractBiFunction
Constructor.
AbstractClassifier<T> - Class in smile.classification
Abstract base class of classifiers.
AbstractClassifier(int[]) - Constructor for class smile.classification.AbstractClassifier
Constructor.
AbstractClassifier(BaseVector<?, ?, ?>) - Constructor for class smile.classification.AbstractClassifier
Constructor.
AbstractClassifier(IntSet) - Constructor for class smile.classification.AbstractClassifier
Constructor.
AbstractFunction - Class in smile.data.formula
This class provides a skeletal implementation of the function term.
AbstractFunction(String, Term) - Constructor for class smile.data.formula.AbstractFunction
Constructor.
AbstractInterpolation - Class in smile.interpolation
Abstract base class of one-dimensional interpolation methods.
AbstractInterpolation(double[], double[]) - Constructor for class smile.interpolation.AbstractInterpolation
Constructor.
AbstractTuple - Class in smile.data
Abstract tuple base class.
AbstractTuple() - Constructor for class smile.data.AbstractTuple
 
accept(int, int, double) - Method in interface smile.math.matrix.DoubleConsumer
Accepts one matrix element and performs the operation on the given arguments.
accept(int, int, float) - Method in interface smile.math.matrix.fp32.FloatConsumer
Accepts one matrix element and performs the operation on the given arguments.
accept(File) - Method in class smile.swing.FileChooser.SimpleFileFilter
 
accuracy - Variable in class smile.validation.ClassificationMetrics
The accuracy on validation data.
Accuracy - Class in smile.deep.metric
The accuracy is the proportion of true results (both true positives and true negatives) in the population.
Accuracy - Class in smile.validation.metric
The accuracy is the proportion of true results (both true positives and true negatives) in the population.
Accuracy() - Constructor for class smile.deep.metric.Accuracy
Constructor.
Accuracy() - Constructor for class smile.validation.metric.Accuracy
 
Accuracy(double) - Constructor for class smile.deep.metric.Accuracy
Constructor.
acf(double[], int) - Static method in interface smile.timeseries.TimeSeries
Autocorrelation function.
acos() - Method in class smile.deep.tensor.Tensor
Returns a new tensor with the arccosine of the elements of input.
acos(String) - Static method in interface smile.data.formula.Terms
The acos(x) term.
acos(Term) - Static method in interface smile.data.formula.Terms
The acos(x) term.
acos_() - Method in class smile.deep.tensor.Tensor
Computes the arccosine of the elements of input in place.
actionPerformed(ActionEvent) - Method in class smile.plot.swing.PlotGrid
 
actionPerformed(ActionEvent) - Method in class smile.swing.table.ButtonCellRenderer
 
actionPerformed(ActionEvent) - Method in class smile.swing.table.ColorCellEditor
 
actionPerformed(ActionEvent) - Method in class smile.swing.table.FontCellEditor
 
actionPerformed(ActionEvent) - Method in class smile.swing.table.TableCopyPasteAdapter
This method is activated on the Keystrokes we are listening to in this implementation.
activation() - Method in record class smile.llm.Transformer.Options
Returns the value of the activation record component.
activation() - Method in record class smile.vision.layer.Conv2dNormActivation.Options
Returns the value of the activation record component.
ActivationFunction - Class in smile.deep.activation
The activation function.
ActivationFunction - Interface in smile.base.mlp
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 - Class in smile.data.formula
The term of a + b expression.
Add(Term, Term) - Constructor for class smile.data.formula.Add
Constructor.
add_(double) - Method in class smile.deep.tensor.Tensor
Returns A += b.
add_(float) - Method in class smile.deep.tensor.Tensor
Returns A += b.
add_(Tensor) - Method in class smile.deep.tensor.Tensor
Returns A += B.
add_(Tensor, double) - Method in class smile.deep.tensor.Tensor
Returns A += alpha * B.
add2(double, double, BigMatrix) - Method in class smile.math.matrix.BigMatrix
Element-wise addition A = alpha * A + beta * B^2
add2(double, double, Matrix) - Method in class smile.math.matrix.Matrix
Element-wise addition A = alpha * A + beta * B^2
add2(float, float, Matrix) - Method in class smile.math.matrix.fp32.Matrix
Element-wise addition A = alpha * A + beta * B^2
addAnchor(String) - Method in interface smile.nlp.AnchorText
Adds a link label to the anchor text.
addAnchor(String) - Method in class smile.nlp.SimpleText
 
addChild(String) - Method in class smile.taxonomy.Concept
Adds a child to this node.
addChild(K[], V, int) - Method in class smile.nlp.Trie.Node
Adds a child.
addChild(Concept) - Method in class smile.taxonomy.Concept
Adds a child to this node.
addDiag(double) - Method in class smile.math.matrix.BigMatrix
A[i, i] += b
addDiag(double) - Method in class smile.math.matrix.Matrix
A[i, i] += b
addDiag(double[]) - Method in class smile.math.matrix.BigMatrix
A[i, i] += b[i]
addDiag(double[]) - Method in class smile.math.matrix.Matrix
A[i, i] += b[i]
addDiag(float) - Method in class smile.math.matrix.fp32.Matrix
A[i, i] += b
addDiag(float[]) - Method in class smile.math.matrix.fp32.Matrix
A[i, i] += b[i]
addEdge(int, int) - Method in class smile.graph.AdjacencyList
 
addEdge(int, int) - Method in class smile.graph.AdjacencyMatrix
 
addEdge(int, int) - Method in interface smile.graph.Graph
Creates a new edge in this graph, going from the source vertex to the target vertex, and returns the created edge.
addEdge(int, int, double) - Method in class smile.graph.AdjacencyList
 
addEdge(int, int, double) - Method in class smile.graph.AdjacencyMatrix
 
addEdge(int, int, double) - Method in interface smile.graph.Graph
Creates a new edge in this graph, going from the source vertex to the target vertex, and returns the created edge.
addEdge(Neuron) - Method in class smile.vq.hebb.Neuron
Adds an edge.
addEdge(Neuron, int) - Method in class smile.vq.hebb.Neuron
Adds an edge.
addExtension(String) - Method in class smile.swing.FileChooser.SimpleFileFilter
Adds a file type "dot" extension to filter against.
addKeywords(String...) - Method in class smile.taxonomy.Concept
Adds a list of synomym to the concept synset.
addNotify() - Method in class smile.swing.Table.RowHeader
 
addPropertyChangeListener(PropertyChangeListener) - Method in class smile.plot.swing.Canvas
Add a PropertyChangeListener to the listener list.
AdjacencyList - Class in smile.graph
An adjacency list representation of a graph.
AdjacencyList(int) - Constructor for class smile.graph.AdjacencyList
Constructor.
AdjacencyList(int, boolean) - Constructor for class smile.graph.AdjacencyList
Constructor.
AdjacencyMatrix - Class in smile.graph
An adjacency matrix representation of a graph.
AdjacencyMatrix(int) - Constructor for class smile.graph.AdjacencyMatrix
Constructor.
AdjacencyMatrix(int, boolean) - Constructor for class smile.graph.AdjacencyMatrix
Constructor.
AdjustedMutualInformation - Class in smile.validation.metric
Adjusted Mutual Information (AMI) for comparing clustering.
AdjustedMutualInformation(AdjustedMutualInformation.Method) - Constructor for class smile.validation.metric.AdjustedMutualInformation
Constructor.
AdjustedMutualInformation.Method - Enum Class in smile.validation.metric
The normalization method.
adjustedR2() - Method in class smile.timeseries.AR
Returns adjusted R2 statistic.
adjustedR2() - Method in class smile.timeseries.ARMA
Returns adjusted R2 statistic.
AdjustedRandIndex - Class in smile.validation.metric
Adjusted Rand Index.
AdjustedRandIndex() - Constructor for class smile.validation.metric.AdjustedRandIndex
 
adjustedRSquared() - Method in class smile.regression.LinearModel
Returns adjusted R2 statistic.
age - Variable in class smile.vq.hebb.Edge
The age of the edges.
age() - Method in class smile.vq.hebb.Neuron
Increments the age of all edges emanating from the neuron.
aggregate(String) - Method in class smile.plot.vega.Field
Sets the aggregation function for the field (e.g., "mean", "sum", "median", "min", "max", "count").
aggregate(String, String, String, String...) - Method in class smile.plot.vega.Transform
Aggregate summarizes a table as one record for each group.
AIC() - Method in class smile.classification.LogisticRegression
Returns the AIC score.
AIC() - Method in class smile.classification.Maxent
Returns the AIC score.
AIC() - Method in class smile.classification.SparseLogisticRegression
Returns the AIC score.
AIC() - Method in class smile.glm.GLM
Returns the AIC score.
AIC(double, int) - Static method in interface smile.validation.ModelSelection
Akaike information criterion.
align(String) - Method in class smile.plot.vega.Concat
 
align(String) - Method in class smile.plot.vega.Facet
 
align(String) - Method in class smile.plot.vega.FacetField
Sets the alignment to apply to row/column facet's subplot.
align(String) - Method in class smile.plot.vega.Repeat
 
align(String) - Method in interface smile.plot.vega.ViewLayoutComposition
Sets the alignment to apply to grid rows and columns.
align(String, String) - Method in class smile.plot.vega.Concat
 
align(String, String) - Method in class smile.plot.vega.Facet
 
align(String, String) - Method in class smile.plot.vega.Repeat
 
align(String, String) - Method in interface smile.plot.vega.ViewLayoutComposition
Sets different alignments for rows and columns.
ALL - Enum constant in enum class smile.math.blas.EigenRange
All eigenvalues will be found.
ALL - Enum constant in enum class smile.math.blas.SVDJob
All left (or right) singular vectors are returned in supplied matrix U (or Vt).
allocate(long) - Static method in class smile.io.Arrow
Creates the root allocator.
allowSpecialTokens(boolean) - Method in class smile.llm.tokenizer.Tiktoken
Sets how special tokens will be encoded.
alpha - Variable in class smile.stat.distribution.BetaDistribution
The shape parameter.
alpha() - Method in class smile.stat.distribution.BetaDistribution
Returns the shape parameter alpha.
AlphaIcon - Class in smile.swing
An Icon wrapper that paints the contained icon with a specified transparency.
AlphaIcon(Icon, float) - Constructor for class smile.swing.AlphaIcon
Creates an AlphaIcon with the specified icon and opacity.
anchor(double) - Method in class smile.plot.vega.BinParams
Sets the value in the binned domain at which to anchor the bins, shifting the bin boundaries if necessary to ensure that a boundary aligns with the anchor value.
AnchorText - Interface in smile.nlp
The anchor text is the visible, clickable text in a hyperlink.
and(Tensor) - Method in class smile.deep.tensor.Tensor
Returns logical AND of two boolean tensors.
and(Predicate...) - Static method in class smile.plot.vega.Predicate
Logical AND composition to combine predicates.
and_(Tensor) - Method in class smile.deep.tensor.Tensor
Returns logical AND of two boolean tensors.
andThen(Transform) - Method in interface smile.data.transform.Transform
Returns a composed function that first applies this function to its input, and then applies the after function to the result.
antecedent - Variable in class smile.association.AssociationRule
Antecedent itemset.
anyNull() - Method in interface smile.data.Tuple
Returns true if there are any NULL values in this tuple.
anyNull() - Method in interface smile.data.vector.Vector
Returns true if there are any NULL values in this row.
append(int, double) - Method in class smile.util.SparseArray
Append an entry to the array, optimizing for the case where the index is greater than all existing indices in the array.
apply(double) - Method in interface smile.math.Function
Computes the value of the function at x.
apply(double) - Method in interface smile.math.kernel.DotProductKernel
Computes the kernel function.
apply(double) - Method in interface smile.math.kernel.IsotropicKernel
Computes the kernel function.
apply(double[]) - Method in class smile.feature.extraction.KernelPCA
 
apply(double[]) - Method in class smile.feature.extraction.Projection
Project a data point to the feature space.
apply(double...) - Method in interface smile.math.MultivariateFunction
Computes the value of the function at x.
apply(double[][]) - Method in class smile.feature.extraction.Projection
Project a set of data to the feature space.
apply(double, FPTree) - Static method in class smile.association.ARM
Mines the association rules.
apply(int) - Method in interface smile.data.DataFrame
Returns the row at the specified index.
apply(int) - Method in interface smile.data.Dataset
Returns the index at the specified index.
apply(int) - Method in interface smile.data.Tuple
Returns the value at position i.
apply(int) - Method in interface smile.data.vector.BaseVector
Returns the value at position i, which may be null.
apply(int) - Method in class smile.math.Complex.Array
Returns the i-th element.
apply(int) - Method in interface smile.math.IntFunction
Computes the value of the function at x.
apply(int) - Method in interface smile.math.TimeFunction
Returns the function value at time step t.
apply(int...) - Method in interface smile.data.vector.BaseVector
Returns a new vector with selected entries.
apply(int, int) - Method in class smile.math.matrix.fp32.IMatrix
Returns A[i,j].
apply(int, int) - Method in class smile.math.matrix.IMatrix
Returns A[i,j] for Scala users.
apply(int, int) - Method in class smile.util.Array2D
Returns A[i, j].
apply(int, int) - Method in class smile.util.IntArray2D
Returns A[i, j].
apply(int, int, int, Fitness<BitString>) - Method in class smile.feature.selection.GAFE
Genetic algorithm based feature selection for classification.
apply(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
apply(String) - Method in interface smile.data.DataFrame
Selects column based on the column name and return it as a Column.
apply(String) - Method in interface smile.data.Tuple
Returns the value by field name.
apply(String) - Method in class smile.feature.extraction.BagOfWords
Returns the bag-of-words features of a document.
apply(String) - Method in class smile.feature.extraction.HashEncoder
Returns the bag-of-words features of a document.
apply(String) - Method in class smile.nlp.embedding.Word2Vec
Returns the embedding vector of a word.
apply(String) - Method in interface smile.nlp.tokenizer.Tokenizer
 
apply(JTable) - Method in class smile.swing.table.TableColumnSettings
Apply this column settings to given table.
apply(JTable) - Static method in class smile.swing.table.TableCopyPasteAdapter
 
apply(FPTree) - Static method in class smile.association.FPGrowth
Mines the frequent item sets.
apply(DataFrame) - Method in interface smile.data.formula.Feature
Applies the term on a data frame.
apply(DataFrame) - Method in class smile.data.transform.ColumnTransform
 
apply(DataFrame) - Method in interface smile.data.transform.Transform
Applies this transform to the given argument.
apply(DataFrame) - Method in class smile.feature.extraction.BinaryEncoder
Generates the compact representation of sparse binary features for a data frame.
apply(DataFrame) - Method in class smile.feature.extraction.Projection
 
apply(DataFrame) - Method in class smile.feature.extraction.SparseEncoder
Generates the sparse representation of a data frame.
apply(DataFrame) - Method in class smile.feature.imputation.SimpleImputer
 
apply(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a tuple.
apply(Tuple) - Method in class smile.data.formula.Formula
Apply the formula on a tuple to generate the model data.
apply(Tuple) - Method in class smile.data.transform.ColumnTransform
 
apply(Tuple) - Method in class smile.feature.extraction.BagOfWords
 
apply(Tuple) - Method in class smile.feature.extraction.BinaryEncoder
Generates the compact representation of sparse binary features for given object.
apply(Tuple) - Method in class smile.feature.extraction.Projection
 
apply(Tuple) - Method in class smile.feature.extraction.SparseEncoder
Generates the sparse representation of given object.
apply(Tuple) - Method in class smile.feature.imputation.KMedoidsImputer
 
apply(Tuple) - Method in class smile.feature.imputation.KNNImputer
 
apply(Tuple) - Method in class smile.feature.imputation.SimpleImputer
 
apply(Tuple) - Method in class smile.feature.transform.Normalizer
 
apply(Tensor) - Method in interface smile.deep.layer.Layer
 
apply(Tensor) - Method in class smile.deep.Model
 
apply(BitString, BitString) - Method in enum class smile.gap.Crossover
Returns a pair of offsprings by crossovering parent chromosomes.
apply(T) - Method in class smile.manifold.KPCA
 
apply(T[]) - Method in interface smile.gap.Selection
Select a chromosome with replacement from the population based on their fitness.
apply(T[]) - Method in class smile.manifold.KPCA
Project a set of data to the feature space.
apply(T, T) - Method in interface smile.math.distance.Distance
Returns the distance measure between two objects.
apply(T, T) - Method in interface smile.math.kernel.MercerKernel
Kernel function.
applyAsBoolean(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a data object and produces 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(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(double, double, double) - Static method in class smile.deep.tensor.Tensor
Returns a 1-D tensor of size (end - start) / step with values from the interval [start, end) taken with common difference step beginning from start.
arange(float, float, float) - Static method in class smile.deep.tensor.Tensor
Returns a 1-D tensor of size (end - start) / step with values from the interval [start, end) taken with common difference step beginning from start.
arange(int, int, int) - Static method in class smile.deep.tensor.Tensor
Returns a 1-D tensor of size (end - start) / step with values from the interval [start, end) taken with common difference step beginning from start.
arange(long, long, long) - Static method in class smile.deep.tensor.Tensor
Returns a 1-D tensor of size (end - start) / step with values from the interval [start, end) taken with common difference step beginning from start.
arff(String) - Static method in interface smile.io.Read
Reads an ARFF file.
arff(Path) - Static method in interface smile.io.Read
Reads an ARFF file.
arff(DataFrame, Path, String) - Static method in interface smile.io.Write
Writes the data frame to an ARFF file.
Arff - Class in smile.io
Weka ARFF (attribute relation file format) is an ASCII text file format that is essentially a CSV file with a header that describes the meta-data.
Arff(Reader) - Constructor for class smile.io.Arff
Constructor.
Arff(String) - Constructor for class smile.io.Arff
Constructor.
Arff(String, Charset) - Constructor for class smile.io.Arff
Constructor.
Arff(Path) - Constructor for class smile.io.Arff
Constructor.
Arff(Path, Charset) - Constructor for class smile.io.Arff
Constructor.
argmax(int, boolean) - Method in class smile.deep.tensor.Tensor
Returns the indices of the maximum value of a tensor across a dimension.
aria(boolean) - Method in class smile.plot.vega.Axis
Sets if ARIA attributes should be included (SVG output only).
aria(boolean) - Method in class smile.plot.vega.Legend
Sets if ARIA attributes should be included (SVG output only).
aria(boolean) - Method in class smile.plot.vega.Mark
Sets the aria.
ARM - Class in smile.association
Association Rule Mining.
ARMA - Class in smile.timeseries
Autoregressive moving-average model.
ARMA(double[], double[], double[], double, double[], double[]) - Constructor for class smile.timeseries.ARMA
Constructor.
ARPACK - Class in smile.math.matrix
ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems.
ARPACK - Class in smile.math.matrix.fp32
ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems.
ARPACK.AsymmOption - Enum Class in smile.math.matrix
Which eigenvalues of asymmetric matrix to compute.
ARPACK.AsymmOption - Enum Class in smile.math.matrix.fp32
Which eigenvalues of asymmetric matrix to compute.
ARPACK.SymmOption - Enum Class in smile.math.matrix
Which eigenvalues of symmetric matrix to compute.
ARPACK.SymmOption - Enum Class in smile.math.matrix.fp32
Which eigenvalues of symmetric matrix to compute.
array() - Method in interface smile.data.vector.BaseVector
Returns the array that backs this vector.
array() - Method in interface smile.data.vector.BooleanVector
 
array() - Method in interface smile.data.vector.ByteVector
 
array() - Method in interface smile.data.vector.CharVector
 
array() - Method in interface smile.data.vector.DoubleVector
 
array() - Method in interface smile.data.vector.FloatVector
 
array() - Method in interface smile.data.vector.IntVector
 
array() - Method in interface smile.data.vector.LongVector
 
array() - Method in interface smile.data.vector.ShortVector
 
array() - Method in record class smile.util.Bytes
Returns the value of the array record component.
array(DataType) - Static method in class smile.data.type.DataTypes
Creates an array data type.
Array - Enum constant in enum class smile.data.type.DataType.ID
Array type ID.
Array(int) - Constructor for class smile.math.Complex.Array
Constructor.
Array2D - Class in smile.util
2-dimensional array of doubles.
Array2D(double[][]) - Constructor for class smile.util.Array2D
Constructor.
Array2D(int, int) - Constructor for class smile.util.Array2D
Constructor of all-zero matrix.
Array2D(int, int, double) - Constructor for class smile.util.Array2D
Constructor.
Array2D(int, int, double[]) - Constructor for class smile.util.Array2D
Constructor.
ArrayType - Class in smile.data.type
Array of primitive data type.
arrow(String) - Static method in interface smile.io.Read
Reads an Apache Arrow file.
arrow(Path) - Static method in interface smile.io.Read
Reads an Apache Arrow file.
arrow(DataFrame, Path) - Static method in interface smile.io.Write
Writes an Apache Arrow file.
Arrow - Class in smile.io
Apache Arrow is a cross-language development platform for in-memory data.
Arrow() - Constructor for class smile.io.Arrow
Constructor.
Arrow(int) - Constructor for class smile.io.Arrow
Constructor.
as() - Method in record class smile.plot.vega.WindowTransformField
Returns the value of the as record component.
as(String...) - Method in class smile.plot.vega.DensityTransform
Sets the output fields for the sample value and corresponding density estimate.
as(String...) - Method in class smile.plot.vega.LoessTransform
Sets the output field names for the smoothed points generated by the loess transform.
as(String...) - Method in class smile.plot.vega.QuantileTransform
Sets the output field names for the probability and quantile values.
as(String...) - Method in class smile.plot.vega.RegressionTransform
Sets the output field names for the smoothed points generated by the loess transform.
asin() - Method in class smile.deep.tensor.Tensor
Returns a new tensor with the arcsine of the elements of input.
asin(String) - Static method in interface smile.data.formula.Terms
The asin(x) term.
asin(Term) - Static method in interface smile.data.formula.Terms
The asin(x) term.
asin_() - Method in class smile.deep.tensor.Tensor
Computes the arcsine of the elements of input in place.
asolve(double[], double[]) - Method in interface smile.math.matrix.IMatrix.Preconditioner
Solve P * x = b for the preconditioner matrix P.
asolve(float[], float[]) - Method in interface smile.math.matrix.fp32.IMatrix.Preconditioner
Solve P * x = b for the preconditioner matrix P.
assistant - Enum constant in enum class smile.llm.llama.Role
AI assistant.
AssociationRule - Class in smile.association
Association rule object.
AssociationRule(int[], int[], double, double, double, double) - Constructor for class smile.association.AssociationRule
Constructor.
asTorch() - Method in class smile.deep.activation.ActivationFunction
 
asTorch() - Method in class smile.deep.layer.AdaptiveAvgPool2dLayer
 
asTorch() - Method in class smile.deep.layer.AvgPool2dLayer
 
asTorch() - Method in class smile.deep.layer.BatchNorm1dLayer
 
asTorch() - Method in class smile.deep.layer.BatchNorm2dLayer
 
asTorch() - Method in class smile.deep.layer.Conv2dLayer
 
asTorch() - Method in class smile.deep.layer.DropoutLayer
 
asTorch() - Method in class smile.deep.layer.EmbeddingLayer
 
asTorch() - Method in class smile.deep.layer.FullyConnectedLayer
 
asTorch() - Method in class smile.deep.layer.GroupNormLayer
 
asTorch() - Method in interface smile.deep.layer.Layer
Returns the PyTorch Module object.
asTorch() - Method in class smile.deep.layer.LayerBlock
 
asTorch() - Method in class smile.deep.layer.MaxPool2dLayer
 
asTorch() - Method in class smile.deep.Model
Returns the PyTorch Module object.
asTorch() - Method in class smile.deep.tensor.Device
Returns the PyTorch device object.
asTorch() - Method in class smile.deep.tensor.Tensor
Returns the PyTorch tensor object.
asTorch() - Method in class smile.llm.PositionalEncoding
 
asTorch() - Method in class smile.vision.layer.StochasticDepth
 
asum(double[]) - Method in interface smile.math.blas.BLAS
Sums the absolute values of the elements of a vector.
asum(float[]) - Method in interface smile.math.blas.BLAS
Sums the absolute values of the elements of a vector.
asum(int, double[], int) - Method in interface smile.math.blas.BLAS
Sums the absolute values of the elements of a vector.
asum(int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
asum(int, float[], int) - Method in interface smile.math.blas.BLAS
Sums the absolute values of the elements of a vector.
asum(int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
ata() - Method in class smile.math.matrix.BigMatrix
Returns A' * A.
ata() - Method in class smile.math.matrix.fp32.Matrix
Returns A' * A.
ata() - Method in class smile.math.matrix.fp32.SparseMatrix
Returns A' * A.
ata() - Method in class smile.math.matrix.Matrix
Returns A' * A.
ata() - Method in class smile.math.matrix.SparseMatrix
Returns A' * A.
atan(String) - Static method in interface smile.data.formula.Terms
The atan(x) term.
atan(Term) - Static method in interface smile.data.formula.Terms
The atan(x) term.
attach(AutoCloseable...) - Method in class smile.util.AutoScope
Attaches resources to this Scope.
attractors - Variable in class smile.clustering.DENCLUE
The density attractor of each observation.
auc - Variable in class smile.validation.ClassificationMetrics
The AUC on validation data.
AUC - Class in smile.validation.metric
The area under the curve (AUC).
AUC() - Constructor for class smile.validation.metric.AUC
 
AutoScope - Class in smile.util
AutoScope allows for predictable, deterministic resource deallocation.
AutoScope(AutoCloseable...) - Constructor for class smile.util.AutoScope
Constructors.
autosize() - Method in class smile.plot.vega.Concat
 
autosize() - Method in class smile.plot.vega.Config
Sets the overall size of the visualization.
autosize() - Method in class smile.plot.vega.Facet
 
autosize() - Method in class smile.plot.vega.Repeat
 
autosize() - Method in class smile.plot.vega.VegaLite
Sets the overall size of the visualization.
autosize() - Method in class smile.plot.vega.View
 
autosize(String, boolean, String) - Method in class smile.plot.vega.Concat
 
autosize(String, boolean, String) - Method in class smile.plot.vega.Config
Sets the overall size of the visualization.
autosize(String, boolean, String) - Method in class smile.plot.vega.Facet
 
autosize(String, boolean, String) - Method in class smile.plot.vega.Repeat
 
autosize(String, boolean, String) - Method in class smile.plot.vega.VegaLite
Sets the overall size of the visualization.
autosize(String, boolean, String) - Method in class smile.plot.vega.View
 
Averaging - Enum Class in smile.deep.metric
The averaging strategy to aggregate binary performance metrics across multi-classes.
avg - Variable in class smile.validation.ClassificationValidations
The average of metrics.
avg - Variable in class smile.validation.RegressionValidations
The average of metrics.
avgDocSize() - Method in interface smile.nlp.Corpus
Returns the average size of documents in the corpus.
avgDocSize() - Method in class smile.nlp.SimpleCorpus
 
avgPool2d(int) - Static method in interface smile.deep.layer.Layer
Returns an average pooling layer that reduces a tensor by combining cells, and assigning the average value of the input cells to the output cell.
AvgPool2dLayer - Class in smile.deep.layer
An average pooling layer that reduces a tensor by combining cells, and assigning the average value of the input cells to the output cell.
AvgPool2dLayer(int) - Constructor for class smile.deep.layer.AvgPool2dLayer
Constructor.
AvgPool2dLayer(int, int) - Constructor for class smile.deep.layer.AvgPool2dLayer
Constructor.
avro(String, InputStream) - Static method in interface smile.io.Read
Reads an Apache Avro file.
avro(String, String) - Static method in interface smile.io.Read
Reads an Apache Avro file.
avro(Path, InputStream) - Static method in interface smile.io.Read
Reads an Apache Avro file.
avro(Path, Path) - Static method in interface smile.io.Read
Reads an Apache Avro file.
Avro - Class in smile.io
Apache Avro is a data serialization system.
Avro(InputStream) - Constructor for class smile.io.Avro
Constructor.
Avro(Path) - Constructor for class smile.io.Avro
Constructor.
Avro(Schema) - Constructor for class smile.io.Avro
Constructor.
axis() - Method in class smile.plot.vega.Config
Returns the axis definition object.
axis() - Method in class smile.plot.vega.Field
Returns the axis definition object.
axis() - Method in class smile.plot.vega.ViewConfig
Returns the axis definition object.
Axis - Class in smile.plot.swing
This class describes an axis of a coordinate system.
Axis - Class in smile.plot.vega
Axes provide axis lines, ticks, and labels to convey how a positional range represents a data range.
Axis(Base, int) - Constructor for class smile.plot.swing.Axis
Constructor.
axpy(double, double[], double[]) - Method in interface smile.math.blas.BLAS
Computes a constant alpha times a vector x plus a vector y.
axpy(double, double[], double[]) - Static method in class smile.math.MathEx
Update an array by adding a multiple of another array y = a * x + y.
axpy(float, float[], float[]) - Method in interface smile.math.blas.BLAS
Computes a constant alpha times a vector x plus a vector y.
axpy(int, double, double[], int, double[], int) - Method in interface smile.math.blas.BLAS
Computes a constant alpha times a vector x plus a vector y.
axpy(int, double, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
axpy(int, float, float[], int, float[], int) - Method in interface smile.math.blas.BLAS
Computes a constant alpha times a vector x plus a vector y.
axpy(int, float, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 

B

b - Variable in class smile.validation.metric.ContingencyTable
The column sum of contingency table.
B - Variable in class smile.vq.BIRCH
The branching factor of non-leaf nodes.
background() - Method in class smile.plot.vega.View
Returns the view background's fill and stroke object.
background(String) - Method in class smile.plot.vega.Concat
 
background(String) - Method in class smile.plot.vega.Config
Sets the background with CSS color property.
background(String) - Method in class smile.plot.vega.Facet
 
background(String) - Method in class smile.plot.vega.Repeat
 
background(String) - Method in class smile.plot.vega.VegaLite
Sets the background of the entire view with CSS color property.
background(String) - Method in class smile.plot.vega.View
 
Background - Class in smile.plot.vega
The view background of a single-view or layer specification.
backpopagateDropout() - Method in class smile.base.mlp.Layer
Propagates the errors back through the (implicit) dropout layer.
backpropagate(boolean) - Method in class smile.base.mlp.MultilayerPerceptron
Propagates the errors back through the network.
backpropagate(double[]) - Method in class smile.base.mlp.HiddenLayer
 
backpropagate(double[]) - Method in class smile.base.mlp.InputLayer
 
backpropagate(double[]) - Method in class smile.base.mlp.Layer
Propagates the errors back to a lower layer.
backpropagate(double[]) - Method in class smile.base.mlp.OutputLayer
 
backward() - Method in class smile.deep.tensor.Tensor
Computes the gradients.
Bag - Class in smile.validation
A bag of random selected samples.
Bag(int[], int[]) - Constructor for class smile.validation.Bag
Constructor.
BagOfWords - Class in smile.feature.extraction
The bag-of-words feature of text used in natural language processing and information retrieval.
BagOfWords(String[], Function<String, String[]>, String[], boolean) - Constructor for class smile.feature.extraction.BagOfWords
Constructor.
BagOfWords(Function<String, String[]>, String[]) - Constructor for class smile.feature.extraction.BagOfWords
Constructor.
BandMatrix - Class in smile.math.matrix
A band matrix is a sparse matrix, whose non-zero entries are confined to a diagonal band, comprising the main diagonal and zero or more diagonals on either side.
BandMatrix - Class in smile.math.matrix.fp32
A band matrix is a sparse matrix, whose non-zero entries are confined to a diagonal band, comprising the main diagonal and zero or more diagonals on either side.
BandMatrix(int, int, int, int) - Constructor for class smile.math.matrix.BandMatrix
Constructor.
BandMatrix(int, int, int, int) - Constructor for class smile.math.matrix.fp32.BandMatrix
Constructor.
BandMatrix(int, int, int, int, double[][]) - Constructor for class smile.math.matrix.BandMatrix
Constructor.
BandMatrix(int, int, int, int, float[][]) - Constructor for class smile.math.matrix.fp32.BandMatrix
Constructor.
BandMatrix.Cholesky - Class in smile.math.matrix
The Cholesky decomposition of a symmetric, positive-definite matrix.
BandMatrix.Cholesky - Class in smile.math.matrix.fp32
The Cholesky decomposition of a symmetric, positive-definite matrix.
BandMatrix.LU - Class in smile.math.matrix
The LU decomposition.
BandMatrix.LU - Class in smile.math.matrix.fp32
The LU decomposition.
bandPosition(double) - Method in class smile.plot.vega.Axis
For band scales, sets the interpolation fraction where axis ticks should be positioned.
bandwidth() - Method in class smile.stat.distribution.KernelDensity
Returns the bandwidth of kernel.
bandwidth(double) - Method in class smile.plot.vega.DensityTransform
Sets the bandwidth (standard deviation) of the Gaussian kernel.
bandwidth(double) - Method in class smile.plot.vega.LoessTransform
Sets a bandwidth parameter in the range [0, 1] that determines the amount of smoothing.
Bar - Class in smile.plot.swing
Bars with heights proportional to the value.
Bar(double[][], double, Color) - Constructor for class smile.plot.swing.Bar
Constructor.
BarPlot - Class in smile.plot.swing
A barplot draws bars with heights proportional to the value.
BarPlot(Bar...) - Constructor for class smile.plot.swing.BarPlot
Constructor.
BarPlot(Bar[], Legend[]) - Constructor for class smile.plot.swing.BarPlot
Constructor.
base(int) - Method in class smile.plot.vega.BinParams
Sets the number base to use for automatic bin determination (default is base 10).
Base - Class in smile.plot.swing
The coordinate base of PlotCanvas.
Base(double[], double[]) - Constructor for class smile.plot.swing.Base
Constructor.
Base(double[], double[], boolean) - Constructor for class smile.plot.swing.Base
Constructor.
BaseVector<T,TS,S> - Interface in smile.data.vector
Base interface for immutable named vectors, which are sequences of elements supporting random access and sequential stream operations.
batch(int) - Method in interface smile.data.Dataset
Returns an iterator of mini-batches.
batchNorm1d(int) - Static method in interface smile.deep.layer.Layer
Returns a normalization layer that re-centers and normalizes the output of one layer before feeding it to another.
batchNorm1d(int, double, double, boolean) - Static method in interface smile.deep.layer.Layer
Returns a normalization layer that re-centers and normalizes the output of one layer before feeding it to another.
BatchNorm1dLayer - Class in smile.deep.layer
A batch normalization layer that re-centers and normalizes the output of one layer before feeding it to another.
BatchNorm1dLayer(int) - Constructor for class smile.deep.layer.BatchNorm1dLayer
Constructor.
BatchNorm1dLayer(int, double, double, boolean) - Constructor for class smile.deep.layer.BatchNorm1dLayer
Constructor.
batchNorm2d(int) - Static method in interface smile.deep.layer.Layer
Returns a normalization layer that re-centers and normalizes the output of one layer before feeding it to another.
batchNorm2d(int, double, double, boolean) - Static method in interface smile.deep.layer.Layer
Returns a normalization layer that re-centers and normalizes the output of one layer before feeding it to another.
BatchNorm2dLayer - Class in smile.deep.layer
A batch normalization layer that re-centers and normalizes the output of one layer before feeding it to another.
BatchNorm2dLayer(int) - Constructor for class smile.deep.layer.BatchNorm2dLayer
Constructor.
BatchNorm2dLayer(int, double, double, boolean) - Constructor for class smile.deep.layer.BatchNorm2dLayer
Constructor.
BBDTree - Class in smile.clustering
Balanced Box-Decomposition Tree.
BBDTree(double[][]) - Constructor for class smile.clustering.BBDTree
Constructs a tree out of the given n data points living in R^d.
BE - Enum constant in enum class smile.math.matrix.ARPACK.SymmOption
Computes nev eigenvalues, half from each end of the spectrum.
BE - Enum constant in enum class smile.math.matrix.fp32.ARPACK.SymmOption
Computes nev eigenvalues, half from each end of the spectrum.
Bernoulli - Interface in smile.glm.model
The response variable is of Bernoulli distribution.
BERNOULLI - Enum constant in enum class smile.classification.DiscreteNaiveBayes.Model
The document Bernoulli model generates an indicator for each term of the vocabulary, either indicating presence of the term in the document or indicating absence.
bernoulli_(double) - Method in class smile.deep.tensor.Tensor
Draws binary random numbers (0 or 1) from a Bernoulli distribution.
BernoulliDistribution - Class in smile.stat.distribution
Bernoulli'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.
BERT - Class in smile.llm
Bidirectional Encoder Representations from Transformers (BERT).
BERT() - Constructor for class smile.llm.BERT
 
BestLocalizedWavelet - Class in smile.wavelet
Best localized wavelets.
BestLocalizedWavelet(int) - Constructor for class smile.wavelet.BestLocalizedWavelet
Constructor.
beta - Variable in class smile.glm.GLM
The linear weights.
beta - Variable in class smile.stat.distribution.BetaDistribution
The shape parameter.
beta() - Method in class smile.stat.distribution.BetaDistribution
Returns the shape parameter beta.
beta(double, double) - Static method in class smile.math.special.Beta
Beta function, also called the Euler integral of the first kind.
Beta - Class in smile.math.special
The beta function, also called the Euler integral of the first kind.
BetaDistribution - Class in smile.stat.distribution
The beta distribution is defined on the interval [0, 1] parameterized by two positive shape parameters, typically denoted by α and β.
BetaDistribution(double, double) - Constructor for class smile.stat.distribution.BetaDistribution
Constructor.
BFGS - Class in smile.math
The Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization problems.
BFGS() - Constructor for class smile.math.BFGS
 
BFloat16 - Enum constant in enum class smile.deep.tensor.ScalarType
The bfloat16 (brain floating point) floating-point format occupies 16 bits.
bfs() - Method in class smile.graph.AdjacencyList
 
bfs() - Method in class smile.graph.AdjacencyMatrix
 
bfs() - Method in interface smile.graph.Graph
Breadth-first search connected components of graph.
bfs(Visitor) - Method in class smile.graph.AdjacencyList
 
bfs(Visitor) - Method in class smile.graph.AdjacencyMatrix
 
bfs(Visitor) - Method in interface smile.graph.Graph
BFS search on graph and performs some operation defined in visitor on each vertex during traveling.
bias - Variable in class smile.base.mlp.Layer
The bias.
biasGradient - Variable in class smile.base.mlp.Layer
The bias gradient.
biasGradientMoment1 - Variable in class smile.base.mlp.Layer
The first moment of bias gradient.
biasGradientMoment2 - Variable in class smile.base.mlp.Layer
The second moment of bias gradient.
biasUpdate - Variable in class smile.base.mlp.Layer
The bias update.
bic - Variable in class smile.stat.distribution.DiscreteExponentialFamilyMixture
The BIC score when the distribution is fit on a sample data.
bic - Variable in class smile.stat.distribution.ExponentialFamilyMixture
The BIC score when the distribution is fit on a sample data.
bic - Variable in class smile.stat.distribution.MultivariateExponentialFamilyMixture
The BIC score when the distribution is fit on a sample data.
bic(double[]) - Method in class smile.stat.distribution.DiscreteMixture
Returns the BIC score.
bic(double[]) - Method in class smile.stat.distribution.Mixture
Returns the BIC score.
bic(double[][]) - Method in class smile.stat.distribution.MultivariateMixture
Returns the BIC score.
BIC() - Method in class smile.glm.GLM
Returns the BIC score.
BIC(double, int, int) - Static method in interface smile.validation.ModelSelection
Bayesian information criterion.
BicubicInterpolation - Class in smile.interpolation
Bicubic interpolation in a two-dimensional regular grid.
BicubicInterpolation(double[], double[], double[][]) - Constructor for class smile.interpolation.BicubicInterpolation
Constructor.
BigMatrix - Class in smile.math.matrix
Big dense matrix of double precision values for more than 2 billion elements.
BigMatrix(int, int) - Constructor for class smile.math.matrix.BigMatrix
Constructor of zero matrix.
BigMatrix(int, int, double) - Constructor for class smile.math.matrix.BigMatrix
Constructor.
BigMatrix(int, int, int, DoublePointer) - Constructor for class smile.math.matrix.BigMatrix
Constructor.
BigMatrix.Cholesky - Class in smile.math.matrix
The Cholesky decomposition of a symmetric, positive-definite matrix.
BigMatrix.EVD - Class in smile.math.matrix
Eigenvalue decomposition.
BigMatrix.LU - Class in smile.math.matrix
The LU decomposition.
BigMatrix.QR - Class in smile.math.matrix
The QR decomposition.
BigMatrix.SVD - Class in smile.math.matrix
Singular Value Decomposition.
Bigram - Class in smile.nlp
Bigrams or digrams are groups of two words, and are very commonly used as the basis for simple statistical analysis of text.
Bigram - Class in smile.nlp.collocation
Collocations are expressions of multiple words which commonly co-occur.
Bigram(String, String) - Constructor for class smile.nlp.Bigram
Constructor.
Bigram(String, String, int, double) - Constructor for class smile.nlp.collocation.Bigram
Constructor.
bigrams() - Method in interface smile.nlp.Corpus
Returns the iterator over the bigrams in the corpus.
bigrams() - Method in class smile.nlp.SimpleCorpus
 
BilinearInterpolation - Class in smile.interpolation
Bilinear interpolation in a two-dimensional regular grid.
BilinearInterpolation(double[], double[], double[][]) - Constructor for class smile.interpolation.BilinearInterpolation
Constructor.
bin(boolean) - Method in class smile.plot.vega.FacetField
Turns on/off binning a quantitative field.
bin(boolean) - Method in class smile.plot.vega.Field
Turns on/off binning a quantitative field.
bin(String) - Method in class smile.plot.vega.FacetField
Indicates that the data for x or y channel are binned before they are imported into Vega-Lite.
bin(String) - Method in class smile.plot.vega.Field
Indicates that the data for x or y channel are binned before they are imported into Vega-Lite.
bin(String, String) - Method in class smile.plot.vega.Transform
Adds a bin transformation.
bin(BinParams) - Method in class smile.plot.vega.Field
Sets custom binning parameters.
binary(int, KernelMachine<int[]>) - Static method in class smile.base.svm.LinearKernelMachine
Creates a linear kernel machine.
binary(String) - Static method in interface smile.math.kernel.MercerKernel
Returns a binary sparse kernel function.
BinaryEncoder - Class in smile.feature.extraction
Encodes categorical features using sparse one-hot scheme.
BinaryEncoder(StructType, String...) - Constructor for class smile.feature.extraction.BinaryEncoder
Constructor.
BinarySparseDataset<T> - Interface in smile.data
Binary sparse dataset.
BinarySparseGaussianKernel - Class in smile.math.kernel
Gaussian kernel, also referred as RBF kernel or squared exponential kernel.
BinarySparseGaussianKernel(double) - Constructor for class smile.math.kernel.BinarySparseGaussianKernel
Constructor.
BinarySparseGaussianKernel(double, double, double) - Constructor for class smile.math.kernel.BinarySparseGaussianKernel
Constructor.
BinarySparseHyperbolicTangentKernel - Class in smile.math.kernel
The hyperbolic tangent kernel on binary sparse data.
BinarySparseHyperbolicTangentKernel() - Constructor for class smile.math.kernel.BinarySparseHyperbolicTangentKernel
Constructor with scale 1.0 and offset 0.0.
BinarySparseHyperbolicTangentKernel(double, double) - Constructor for class smile.math.kernel.BinarySparseHyperbolicTangentKernel
Constructor.
BinarySparseHyperbolicTangentKernel(double, double, double[], double[]) - Constructor for class smile.math.kernel.BinarySparseHyperbolicTangentKernel
Constructor.
BinarySparseLaplacianKernel - Class in smile.math.kernel
Laplacian kernel, also referred as exponential kernel.
BinarySparseLaplacianKernel(double) - Constructor for class smile.math.kernel.BinarySparseLaplacianKernel
Constructor.
BinarySparseLaplacianKernel(double, double, double) - Constructor for class smile.math.kernel.BinarySparseLaplacianKernel
Constructor.
BinarySparseLinearKernel - Class in smile.math.kernel
The linear dot product kernel on sparse binary arrays in int[], which are the indices of nonzero elements.
BinarySparseLinearKernel() - Constructor for class smile.math.kernel.BinarySparseLinearKernel
Constructor.
BinarySparseMaternKernel - Class in smile.math.kernel
The class of Matérn kernels is a generalization of the Gaussian/RBF.
BinarySparseMaternKernel(double, double) - Constructor for class smile.math.kernel.BinarySparseMaternKernel
Constructor.
BinarySparseMaternKernel(double, double, double, double) - Constructor for class smile.math.kernel.BinarySparseMaternKernel
Constructor.
BinarySparsePolynomialKernel - Class in smile.math.kernel
The polynomial kernel on binary sparse data.
BinarySparsePolynomialKernel(int) - Constructor for class smile.math.kernel.BinarySparsePolynomialKernel
Constructor with scale 1 and offset 0.
BinarySparsePolynomialKernel(int, double, double) - Constructor for class smile.math.kernel.BinarySparsePolynomialKernel
Constructor.
BinarySparsePolynomialKernel(int, double, double, double[], double[]) - Constructor for class smile.math.kernel.BinarySparsePolynomialKernel
Constructor.
BinarySparseThinPlateSplineKernel - Class in smile.math.kernel
The Thin Plate Spline kernel on binary sparse data.
BinarySparseThinPlateSplineKernel(double) - Constructor for class smile.math.kernel.BinarySparseThinPlateSplineKernel
Constructor.
BinarySparseThinPlateSplineKernel(double, double, double) - Constructor for class smile.math.kernel.BinarySparseThinPlateSplineKernel
Constructor.
bind(StructType) - Method in class smile.data.formula.Abs
 
bind(StructType) - Method in class smile.data.formula.Add
 
bind(StructType) - Method in class smile.data.formula.Date
 
bind(StructType) - Method in class smile.data.formula.Div
 
bind(StructType) - Method in class smile.data.formula.DoubleFunction
 
bind(StructType) - Method in class smile.data.formula.FactorCrossing
 
bind(StructType) - Method in class smile.data.formula.FactorInteraction
 
bind(StructType) - Method in class smile.data.formula.Formula
Binds the formula to a schema and returns the schema of predictors.
bind(StructType) - Method in class smile.data.formula.IntFunction
 
bind(StructType) - Method in class smile.data.formula.Mul
 
bind(StructType) - Method in class smile.data.formula.Sub
 
bind(StructType) - Method in interface smile.data.formula.Term
Binds the term to a schema.
binomial(double[][], int[]) - Static method in class smile.classification.LogisticRegression
Fits binomial logistic regression.
binomial(double[][], int[], double, double, int) - Static method in class smile.classification.LogisticRegression
Fits binomial logistic regression.
binomial(double[][], int[], Properties) - Static method in class smile.classification.LogisticRegression
Fits binomial logistic regression.
binomial(int, int[][], int[]) - Static method in class smile.classification.Maxent
Fits maximum entropy classifier.
binomial(int, int[][], int[], double, double, int) - Static method in class smile.classification.Maxent
Fits maximum entropy classifier.
binomial(int, int[][], int[], Properties) - Static method in class smile.classification.Maxent
Fits maximum entropy classifier.
binomial(SparseDataset<Integer>) - Static method in class smile.classification.SparseLogisticRegression
Fits binomial logistic regression.
binomial(SparseDataset<Integer>, double, double, int) - Static method in class smile.classification.SparseLogisticRegression
Fits binomial logistic regression.
binomial(SparseDataset<Integer>, Properties) - Static method in class smile.classification.SparseLogisticRegression
Fits binomial logistic regression.
Binomial - Interface in smile.glm.model
The response variable is of Binomial distribution.
Binomial(double[], double, double, IntSet) - Constructor for class smile.classification.LogisticRegression.Binomial
Constructor.
Binomial(double[], double, double, IntSet) - Constructor for class smile.classification.Maxent.Binomial
Constructor.
Binomial(double[], double, double, IntSet) - Constructor for class smile.classification.SparseLogisticRegression.Binomial
Constructor.
BinomialDistribution - Class in smile.stat.distribution
The binomial distribution is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p.
BinomialDistribution(int, double) - Constructor for class smile.stat.distribution.BinomialDistribution
Constructor.
BinParams - Class in smile.plot.vega
To test a data point in a filter transform or a test property in conditional encoding, a predicate definition of the following forms must be specified: - a Vega expression string, where datum can be used to refer to the current data object.
BinParams() - Constructor for class smile.plot.vega.BinParams
Constructor.
bins(double[], double) - Static method in interface smile.math.Histogram
Returns the number of bins for a data based on a suggested bin width h.
bins(int) - Static method in interface smile.math.Histogram
Returns the number of bins by square-root rule, which takes the square root of the number of data points in the sample (used by Excel histograms and many others).
BIRCH - Class in smile.vq
Balanced Iterative Reducing and Clustering using Hierarchies.
BIRCH(int, int, int, double) - Constructor for class smile.vq.BIRCH
Constructor.
bits() - Method in class smile.gap.BitString
Returns the bit string of chromosome.
BitString - Class in smile.gap
The standard bit string representation of the solution domain.
BitString(byte[], Fitness<BitString>) - Constructor for class smile.gap.BitString
Constructor.
BitString(byte[], Fitness<BitString>, Crossover, double, double) - Constructor for class smile.gap.BitString
Constructor.
BitString(int, Fitness<BitString>) - Constructor for class smile.gap.BitString
Constructor.
BitString(int, Fitness<BitString>, Crossover, double, double) - Constructor for class smile.gap.BitString
Constructor.
bk() - Method in class smile.math.matrix.fp32.SymmMatrix
Bunch-Kaufman decomposition.
bk() - Method in class smile.math.matrix.SymmMatrix
Bunch-Kaufman decomposition.
BKTree<K,V> - Class in smile.neighbor
A BK-tree is a metric tree specifically adapted to discrete metric spaces.
BKTree(Metric<K>) - Constructor for class smile.neighbor.BKTree
Constructor.
BLACK - Static variable in interface smile.plot.swing.Palette
 
blas() - Method in enum class smile.math.blas.Diag
Returns the int value for BLAS.
blas() - Method in enum class smile.math.blas.Layout
Returns the int value for BLAS.
blas() - Method in enum class smile.math.blas.Side
Returns the int value for BLAS.
blas() - Method in enum class smile.math.blas.Transpose
Returns the int value for BLAS.
blas() - Method in enum class smile.math.blas.UPLO
Returns the int value for BLAS.
BLAS - Interface in smile.math.blas
Basic Linear Algebra Subprograms.
blend(String) - Method in class smile.plot.vega.Mark
Sets the color blend mode for drawing an item on its current background.
block() - Method in record class smile.vision.layer.MBConvConfig
Returns the value of the block record component.
BLUE - Static variable in interface smile.plot.swing.Palette
 
BM25 - Class in smile.nlp.relevance
The BM25 weighting scheme, often called Okapi weighting, after the system in which it was first implemented, was developed as a way of building a probabilistic model sensitive to term frequency and document length while not introducing too many additional parameters into the model.
BM25() - Constructor for class smile.nlp.relevance.BM25
Default constructor with k1 = 1.2, b = 0.75, delta = 1.0.
BM25(double, double, double) - Constructor for class smile.nlp.relevance.BM25
Constructor.
body - Variable in class smile.nlp.Text
The text body.
Boolean - Enum constant in enum class smile.data.type.DataType.ID
Boolean type ID.
BOOLEAN - Static variable in interface smile.util.Regex
Boolean regular expression pattern.
BOOLEAN_REGEX - Static variable in interface smile.util.Regex
Boolean regular expression.
BooleanArrayType - Static variable in class smile.data.type.DataTypes
Boolean Array data type.
BooleanObjectType - Static variable in class smile.data.type.DataTypes
Boolean Object data type.
BooleanType - Class in smile.data.type
Boolean data type.
BooleanType - Static variable in class smile.data.type.DataTypes
Boolean data type.
booleanVector(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
booleanVector(int) - Method in class smile.data.IndexDataFrame
 
booleanVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
booleanVector(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
BooleanVector - Interface in smile.data.vector
An immutable boolean vector.
Bootstrap - Interface in smile.validation
The bootstrap is a general tool for assessing statistical accuracy.
bounds(String) - Method in class smile.plot.vega.Concat
 
bounds(String) - Method in class smile.plot.vega.Facet
 
bounds(String) - Method in class smile.plot.vega.Repeat
 
bounds(String) - Method in interface smile.plot.vega.ViewLayoutComposition
Sets the bounds calculation method to use for determining the extent of a sub-plot.
Box_Pierce - Enum constant in enum class smile.timeseries.BoxTest.Type
Box-Pierce test.
boxed() - Method in interface smile.data.type.DataType
Returns the boxed data type if this is a primitive type.
boxed(Collection<Tuple>) - Method in class smile.data.type.StructType
Updates the field type to the boxed one if the field has null/missing values in the data.
BoxPlot - Class in smile.plot.swing
A boxplot is a convenient way of graphically depicting groups of numerical data through their five-number summaries the smallest observation (sample minimum), lower quartile (Q1), median (Q2), upper quartile (Q3), and largest observation (sample maximum).
BoxPlot(double[][], String[]) - Constructor for class smile.plot.swing.BoxPlot
Constructor.
BoxTest - Class in smile.timeseries
Portmanteau test jointly that several autocorrelations of time series are zero.
BoxTest.Type - Enum Class in smile.timeseries
The type of test.
branch(Tuple) - Method in class smile.base.cart.InternalNode
Returns true if the instance goes to the true branch.
branch(Tuple) - Method in class smile.base.cart.NominalNode
 
branch(Tuple) - Method in class smile.base.cart.OrdinalNode
 
BreakIteratorSentenceSplitter - Class in smile.nlp.tokenizer
A sentence splitter based on the java.text.BreakIterator, which supports multiple natural languages (selected by locale setting).
BreakIteratorSentenceSplitter() - Constructor for class smile.nlp.tokenizer.BreakIteratorSentenceSplitter
Constructor for the default locale.
BreakIteratorSentenceSplitter(Locale) - Constructor for class smile.nlp.tokenizer.BreakIteratorSentenceSplitter
Constructor for the given locale.
BreakIteratorTokenizer - Class in smile.nlp.tokenizer
A word tokenizer based on the java.text.BreakIterator, which supports multiple natural languages (selected by locale setting).
BreakIteratorTokenizer() - Constructor for class smile.nlp.tokenizer.BreakIteratorTokenizer
Constructor for the default locale.
BreakIteratorTokenizer(Locale) - Constructor for class smile.nlp.tokenizer.BreakIteratorTokenizer
Constructor for the given locale.
breaks - Variable in class smile.feature.selection.InformationValue
Breakpoints of intervals for numerical variables.
breaks(double[], double) - Static method in interface smile.math.Histogram
Returns the breakpoints between histogram cells for a dataset based on a suggested bin width h.
breaks(double[], int) - Static method in interface smile.math.Histogram
Returns the breakpoints between histogram cells for a dataset.
breaks(double, double, double) - Static method in interface smile.math.Histogram
Returns the breakpoints between histogram cells for a given range based on a suggested bin width h.
breaks(double, double, int) - Static method in interface smile.math.Histogram
Returns the breakpoints between histogram cells for a given range.
BROWN - Static variable in interface smile.plot.swing.Palette
 
bubble(int) - Static method in interface smile.vq.Neighborhood
Returns the bubble neighborhood function.
bucket - Variable in class smile.neighbor.lsh.Bucket
The bucket id is given by the universal bucket hashing.
Bucket - Class in smile.neighbor.lsh
A bucket is a container for points that all have the same value for hash function g (function g is a vector of k LSH functions).
Bucket(int) - Constructor for class smile.neighbor.lsh.Bucket
Constructor.
build() - Method in class smile.hash.PerfectMap.Builder
Builds the perfect map.
build(int) - Method in class smile.base.mlp.HiddenLayerBuilder
 
build(int) - Method in class smile.base.mlp.LayerBuilder
Builds a layer.
build(int) - Method in class smile.base.mlp.OutputLayerBuilder
 
builder(String, int, double, double) - Static method in class smile.base.mlp.Layer
Returns a hidden layer.
Builder() - Constructor for class smile.hash.PerfectMap.Builder
Constructor.
Builder(Map<String, T>) - Constructor for class smile.hash.PerfectMap.Builder
Constructor.
BunchKaufman(SymmMatrix, int[], int) - Constructor for class smile.math.matrix.fp32.SymmMatrix.BunchKaufman
Constructor.
BunchKaufman(SymmMatrix, int[], int) - Constructor for class smile.math.matrix.SymmMatrix.BunchKaufman
Constructor.
BURGUNDY - Static variable in interface smile.plot.swing.Palette
 
Button - Class in smile.swing
Action initialized JButton.
Button(Action) - Constructor for class smile.swing.Button
Constructor.
ButtonCellRenderer - Class in smile.swing.table
The ButtonCellRenderer class provides a renderer and an editor that looks like a JButton.
ButtonCellRenderer(JTable, Action, int) - Constructor for class smile.swing.table.ButtonCellRenderer
Create the ButtonCellRenderer to be used as a renderer and editor.
Byte - Enum constant in enum class smile.data.type.DataType.ID
Byte type ID.
ByteArrayCellRenderer - Class in smile.swing.table
Byte array renderer in JTable.
ByteArrayCellRenderer() - Constructor for class smile.swing.table.ByteArrayCellRenderer
Constructor.
ByteArrayType - Static variable in class smile.data.type.DataTypes
Byte Array data type.
ByteObjectType - Static variable in class smile.data.type.DataTypes
Byte Object data type.
Bytes - Record Class in smile.util
Byte string.
Bytes(byte[]) - Constructor for record class smile.util.Bytes
Creates an instance of a Bytes record class.
Bytes(String) - Constructor for record class smile.util.Bytes
Constructor with a string input.
ByteType - Class in smile.data.type
Byte data type.
ByteType - Static variable in class smile.data.type.DataTypes
Byte data type.
byteValue() - Method in class smile.deep.tensor.Tensor
Returns the byte value when the tensor holds a single value.
byteVector(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
byteVector(int) - Method in class smile.data.IndexDataFrame
 
byteVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
byteVector(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
ByteVector - Interface in smile.data.vector
An immutable byte vector.

C

c(double...) - Static method in class smile.math.MathEx
Combines the arguments to form a vector.
c(double[]...) - Static method in class smile.math.MathEx
Concatenates multiple vectors into one.
c(float...) - Static method in class smile.math.MathEx
Combines the arguments to form a vector.
c(float[]...) - Static method in class smile.math.MathEx
Concatenates multiple vectors into one.
c(int...) - Static method in class smile.math.MathEx
Combines the arguments to form a vector.
c(int[]...) - Static method in class smile.math.MathEx
Concatenates multiple vectors into one.
c(String...) - Static method in class smile.math.MathEx
Combines the arguments to form a vector.
c(String[]...) - Static method in class smile.math.MathEx
Concatenates multiple vectors into one array of strings.
CacheFiles - Interface in smile.util
Static methods that manage cache files.
CADET_BLUE - Static variable in interface smile.plot.swing.Palette
 
calculate(String, String) - Method in class smile.plot.vega.Transform
Adds a formula transform extends data objects with new fields (columns) according to an expression.
CANCEL_OPTION - Static variable in class smile.swing.FontChooser
Return value from showDialog().
canvas() - Method in class smile.plot.swing.BarPlot
 
canvas() - Method in class smile.plot.swing.BoxPlot
 
canvas() - Method in class smile.plot.swing.Contour
 
canvas() - Method in class smile.plot.swing.Dendrogram
 
canvas() - Method in class smile.plot.swing.Heatmap
 
canvas() - Method in class smile.plot.swing.Hexmap
 
canvas() - Method in class smile.plot.swing.LinePlot
 
canvas() - Method in class smile.plot.swing.Plot
Returns a canvas of the plot.
canvas() - Method in class smile.plot.swing.ScreePlot
 
canvas() - Method in class smile.plot.swing.SparseMatrixPlot
 
canvas() - Method in class smile.plot.swing.StaircasePlot
 
Canvas - Class in smile.plot.swing
Canvas for mathematical plots.
Canvas(double[], double[]) - Constructor for class smile.plot.swing.Canvas
Constructor
Canvas(double[], double[], boolean) - Constructor for class smile.plot.swing.Canvas
Constructor
CARDINAL_NUMBER - Static variable in interface smile.util.Regex
Cardinal numbers.
CARDINAL_NUMBER_WITH_COMMA - Static variable in interface smile.util.Regex
Cardinal numbers, optionally thousands are separated by comma.
CART - Class in smile.base.cart
Classification and regression tree.
CART(DataFrame, StructField, int, int, int, int, int[], int[][]) - Constructor for class smile.base.cart.CART
Constructor.
CART(Formula, StructType, StructField, Node, double[]) - Constructor for class smile.base.cart.CART
Constructor.
CategoricalEncoder - Enum Class in smile.data
Categorical variable encoder.
CategoricalMeasure - Class in smile.data.measure
Categorical data can be stored into groups or categories with the aid of names or labels.
CategoricalMeasure(int[]) - Constructor for class smile.data.measure.CategoricalMeasure
Constructor.
CategoricalMeasure(int[], String[]) - Constructor for class smile.data.measure.CategoricalMeasure
Constructor.
CategoricalMeasure(String...) - Constructor for class smile.data.measure.CategoricalMeasure
Constructor.
CategoricalMeasure(List<String>) - Constructor for class smile.data.measure.CategoricalMeasure
Constructor.
cbind(double[]...) - Static method in class smile.math.MathEx
Concatenates vectors by columns.
cbind(float[]...) - Static method in class smile.math.MathEx
Concatenates vectors by columns.
cbind(int[]...) - Static method in class smile.math.MathEx
Concatenates vectors by columns.
cbind(String[]...) - Static method in class smile.math.MathEx
Concatenates vectors by columns.
cbrt(String) - Static method in interface smile.data.formula.Terms
The cbrt(x) term.
cbrt(Term) - Static method in interface smile.data.formula.Terms
The cbrt(x) term.
CC - Enum constant in enum class smile.nlp.pos.PennTreebankPOS
Coordinating conjunction.
CD - Enum constant in enum class smile.nlp.pos.PennTreebankPOS
Cardinal number.
cdf(double) - Method in class smile.stat.distribution.BernoulliDistribution
 
cdf(double) - Method in class smile.stat.distribution.BetaDistribution
 
cdf(double) - Method in class smile.stat.distribution.BinomialDistribution
 
cdf(double) - Method in class smile.stat.distribution.ChiSquareDistribution
 
cdf(double) - Method in class smile.stat.distribution.DiscreteMixture
 
cdf(double) - Method in interface smile.stat.distribution.Distribution
Cumulative distribution function.
cdf(double) - Method in class smile.stat.distribution.EmpiricalDistribution
 
cdf(double) - Method in class smile.stat.distribution.ExponentialDistribution
 
cdf(double) - Method in class smile.stat.distribution.FDistribution
 
cdf(double) - Method in class smile.stat.distribution.GammaDistribution
 
cdf(double) - Method in class smile.stat.distribution.GaussianDistribution
 
cdf(double) - Method in class smile.stat.distribution.GeometricDistribution
 
cdf(double) - Method in class smile.stat.distribution.HyperGeometricDistribution
 
cdf(double) - Method in class smile.stat.distribution.KernelDensity
Cumulative distribution function.
cdf(double) - Method in class smile.stat.distribution.LogisticDistribution
 
cdf(double) - Method in class smile.stat.distribution.LogNormalDistribution
 
cdf(double) - Method in class smile.stat.distribution.Mixture
 
cdf(double) - Method in class smile.stat.distribution.NegativeBinomialDistribution
 
cdf(double) - Method in class smile.stat.distribution.PoissonDistribution
 
cdf(double) - Method in class smile.stat.distribution.ShiftedGeometricDistribution
 
cdf(double) - Method in class smile.stat.distribution.TDistribution
 
cdf(double) - Method in class smile.stat.distribution.WeibullDistribution
 
cdf(double[]) - Method in interface smile.stat.distribution.MultivariateDistribution
Cumulative distribution function.
cdf(double[]) - Method in class smile.stat.distribution.MultivariateGaussianDistribution
Algorithm from Alan Genz (1992) Numerical Computation of Multivariate Normal Probabilities, Journal of Computational and Graphical Statistics, pp.
cdf(double[]) - Method in class smile.stat.distribution.MultivariateMixture
 
cdf2tailed(double) - Method in class smile.stat.distribution.TDistribution
Two-tailed cdf.
ceil(String) - Static method in interface smile.data.formula.Terms
The ceil(x) term.
ceil(Term) - Static method in interface smile.data.formula.Terms
The ceil(x) term.
center() - Method in class smile.feature.extraction.PCA
Returns the center of data.
center() - Method in class smile.feature.extraction.ProbabilisticPCA
Returns the center of data.
center(boolean) - Method in class smile.plot.vega.Concat
 
center(boolean) - Method in class smile.plot.vega.Facet
 
center(boolean) - Method in class smile.plot.vega.FacetField
Sets if facet's subviews should be centered relative to their respective rows or columns.
center(boolean) - Method in class smile.plot.vega.Repeat
 
center(boolean) - Method in interface smile.plot.vega.ViewLayoutComposition
Sets if subviews should be centered relative to their respective rows or columns.
center(double, double) - Method in class smile.plot.vega.Projection
Sets the projection's center, a two-element array of longitude and latitude in degrees.
center(int, int) - Method in class smile.plot.vega.Concat
 
center(int, int) - Method in class smile.plot.vega.Facet
 
center(int, int) - Method in class smile.plot.vega.Repeat
 
center(int, int) - Method in interface smile.plot.vega.ViewLayoutComposition
Sets if subviews should be centered relative to their respective rows or columns.
CentroidClustering<T,U> - Class in smile.clustering
In centroid-based clustering, clusters are represented by a central vector, which may not necessarily be a member of the data set.
CentroidClustering(double, T[], int[]) - Constructor for class smile.clustering.CentroidClustering
Constructor.
centroids - Variable in class smile.clustering.CentroidClustering
The centroids of each cluster.
centroids() - Method in class smile.vq.BIRCH
Returns the cluster centroids of leaf nodes.
change(int) - Method in class smile.util.PriorityQueue
The priority of item k has changed.
Char - Enum constant in enum class smile.data.type.DataType.ID
Char type ID.
CharArrayType - Static variable in class smile.data.type.DataTypes
Char Array data type.
CharObjectType - Static variable in class smile.data.type.DataTypes
Char Object data type.
charset(Charset) - Method in class smile.io.CSV
Sets the charset.
charset(Charset) - Method in class smile.io.JSON
Sets the charset.
CharType - Class in smile.data.type
Char data type.
CharType - Static variable in class smile.data.type.DataTypes
Char data type.
charVector(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
charVector(int) - Method in class smile.data.IndexDataFrame
 
charVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
charVector(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
CharVector - Interface in smile.data.vector
An immutable char vector.
ChebyshevDistance - Class in smile.math.distance
Chebyshev distance (or Tchebychev distance), or L metric is a metric defined on a vector space where the distance between two vectors is the greatest of their differences along any coordinate dimension.
ChebyshevDistance() - Constructor for class smile.math.distance.ChebyshevDistance
Constructor.
children() - Method in class smile.taxonomy.Concept
Gets all children concepts.
chisq - Variable in class smile.stat.hypothesis.ChiSqTest
chi-square statistic
ChiSqTest - Class in smile.stat.hypothesis
Pearson's chi-square test, also known as the chi-square goodness-of-fit test or chi-square test for independence.
ChiSqTest(String, double, double, double) - Constructor for class smile.stat.hypothesis.ChiSqTest
Constructor.
ChiSqTest(String, double, double, double, double) - Constructor for class smile.stat.hypothesis.ChiSqTest
Constructor.
ChiSquareDistribution - Class in smile.stat.distribution
Chi-square (or chi-squared) distribution with k degrees of freedom is the distribution of a sum of the squares of k independent standard normal random variables.
ChiSquareDistribution(int) - Constructor for class smile.stat.distribution.ChiSquareDistribution
Constructor.
cholesky() - Method in class smile.math.matrix.BandMatrix
Cholesky decomposition for symmetric and positive definite matrix.
cholesky() - Method in class smile.math.matrix.BigMatrix
Cholesky decomposition for symmetric and positive definite matrix.
cholesky() - Method in class smile.math.matrix.fp32.BandMatrix
Cholesky decomposition for symmetric and positive definite matrix.
cholesky() - Method in class smile.math.matrix.fp32.Matrix
Cholesky decomposition for symmetric and positive definite matrix.
cholesky() - Method in class smile.math.matrix.fp32.SymmMatrix
Cholesky decomposition for symmetric and positive definite matrix.
cholesky() - Method in class smile.math.matrix.Matrix
Cholesky decomposition for symmetric and positive definite matrix.
cholesky() - Method in class smile.math.matrix.SymmMatrix
Cholesky decomposition for symmetric and positive definite matrix.
cholesky(boolean) - Method in class smile.math.matrix.BigMatrix
Cholesky decomposition for symmetric and positive definite matrix.
cholesky(boolean) - Method in class smile.math.matrix.fp32.Matrix
Cholesky decomposition for symmetric and positive definite matrix.
cholesky(boolean) - Method in class smile.math.matrix.Matrix
Cholesky decomposition for symmetric and positive definite matrix.
Cholesky(BandMatrix) - Constructor for class smile.math.matrix.BandMatrix.Cholesky
Constructor.
Cholesky(BigMatrix) - Constructor for class smile.math.matrix.BigMatrix.Cholesky
Constructor.
Cholesky(BandMatrix) - Constructor for class smile.math.matrix.fp32.BandMatrix.Cholesky
Constructor.
Cholesky(Matrix) - Constructor for class smile.math.matrix.fp32.Matrix.Cholesky
Constructor.
Cholesky(SymmMatrix) - Constructor for class smile.math.matrix.fp32.SymmMatrix.Cholesky
Constructor.
Cholesky(Matrix) - Constructor for class smile.math.matrix.Matrix.Cholesky
Constructor.
Cholesky(SymmMatrix) - Constructor for class smile.math.matrix.SymmMatrix.Cholesky
Constructor.
CholeskyOfAtA() - Method in class smile.math.matrix.BigMatrix.QR
Returns the Cholesky decomposition of A'A.
CholeskyOfAtA() - Method in class smile.math.matrix.fp32.Matrix.QR
Returns the Cholesky decomposition of A'A.
CholeskyOfAtA() - Method in class smile.math.matrix.Matrix.QR
Returns the Cholesky decomposition of A'A.
choose(int, int) - Static method in class smile.math.MathEx
The n choose k.
Chromosome - Interface in smile.gap
Artificial chromosomes in genetic algorithm/programming encoding candidate solutions to an optimization problem.
CLARANS<T> - Class in smile.clustering
Clustering Large Applications based upon RANdomized Search.
CLARANS(double, T[], int[], Distance<T>) - Constructor for class smile.clustering.CLARANS
Constructor.
classes - Variable in class smile.classification.AbstractClassifier
The class labels.
classes - Variable in class smile.classification.ClassLabels
The class labels.
classes() - Method in class smile.classification.AbstractClassifier
 
classes() - Method in interface smile.classification.Classifier
Returns the class labels.
classes() - Method in class smile.classification.DecisionTree
 
classes() - Method in class smile.classification.MLP
 
classes() - Method in class smile.classification.SVM
 
classification(int, int) - Static method in interface smile.vision.transform.Transform
Returns a transform for image classification.
classification(int, int, float[], float[], int) - Static method in interface smile.vision.transform.Transform
Returns a transform for image classification.
classification(int, int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.CrossValidation
Repeated cross validation of classification.
classification(int, int, T[], int[], BiFunction<T[], int[], M>) - Static method in interface smile.validation.CrossValidation
Repeated cross validation of classification.
classification(int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.Bootstrap
Runs classification bootstrap validation.
classification(int, Formula, DataFrame, BiFunction<Formula, DataFrame, M>) - Static method in interface smile.validation.CrossValidation
Cross validation of classification.
classification(int, T[], int[], BiFunction<T[], int[], M>) - Static method in interface smile.validation.Bootstrap
Runs classification bootstrap validation.
classification(int, T[], int[], BiFunction<T[], int[], M>) - Static method in interface smile.validation.CrossValidation
Cross validation of classification.
classification(Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in interface smile.validation.LOOCV
Runs leave-one-out cross validation tests.
classification(T[], int[], BiFunction<T[], int[], M>) - Static method in interface smile.validation.LOOCV
Runs leave-one-out cross validation tests.
CLASSIFICATION_ERROR - Enum constant in enum class smile.base.cart.SplitRule
Classification error.
ClassificationMetric - Interface in smile.validation.metric
An abstract interface to measure the classification performance.
ClassificationMetrics - Class in smile.validation
The classification validation metrics.
ClassificationMetrics(double, double, int, int, double) - Constructor for class smile.validation.ClassificationMetrics
Constructor.
ClassificationMetrics(double, double, int, int, double, double) - Constructor for class smile.validation.ClassificationMetrics
Constructor of multiclass soft classifier validation.
ClassificationMetrics(double, double, int, int, double, double, double, double, double, double) - Constructor for class smile.validation.ClassificationMetrics
Constructor of binary classifier validation.
ClassificationMetrics(double, double, int, int, double, double, double, double, double, double, double, double) - Constructor for class smile.validation.ClassificationMetrics
Constructor of binary soft classifier validation.
ClassificationMetrics(double, double, int, int, double, double, double, double, double, double, double, double, double) - Constructor for class smile.validation.ClassificationMetrics
Constructor.
ClassificationValidation<M> - Class in smile.validation
Classification model validation results.
ClassificationValidation(M, double, double, int[], int[]) - Constructor for class smile.validation.ClassificationValidation
Constructor.
ClassificationValidation(M, double, double, int[], int[], double[][]) - Constructor for class smile.validation.ClassificationValidation
Constructor of soft classifier validation.
ClassificationValidations<M> - Class in smile.validation
Classification model validation results.
ClassificationValidations(List<ClassificationValidation<M>>) - Constructor for class smile.validation.ClassificationValidations
Constructor.
Classifier<T> - Interface in smile.classification
A classifier assigns an input object into one of a given number of categories.
Classifier.Trainer<T,M> - Interface in smile.classification
The classifier trainer.
ClassLabels - Class in smile.classification
Map arbitrary class labels to [0, k), where k is the number of classes.
ClassLabels(int, int[], IntSet) - Constructor for class smile.classification.ClassLabels
Constructor.
clean() - Static method in interface smile.util.CacheFiles
Cleans up the cache directory.
clear() - Method in class smile.base.cart.CART
Clear the workspace of building tree.
clear() - Method in class smile.plot.swing.Canvas
Remove all graphic plots from the canvas.
clear() - Method in class smile.util.DoubleArrayList
Removes all the values from this list.
clear() - Method in class smile.util.IntArrayList
Removes all the values from this list.
clear(double) - Method in class smile.vq.NeuralMap
Removes staled neurons and the edges beyond lifetime.
clearClip() - Method in class smile.plot.swing.Graphics
Clear the restriction of the draw area.
clip() - Method in class smile.plot.swing.Graphics
Restrict the draw area to the valid base coordinate space.
clip(boolean) - Method in class smile.plot.vega.Mark
Sets whether a mark be clipped to the enclosing group's width and height.
clipAngle(double) - Method in class smile.plot.vega.Projection
Sets the projection's clipping circle radius to the specified angle in degrees.
clipExtent(double, double, double, double) - Method in class smile.plot.vega.Projection
Sets the projection's viewport clip extent to the specified bounds in pixels.
clipHeight(double) - Method in class smile.plot.vega.Legend
Sets the height in pixels to clip symbol legend entries and limit their size.
clipNorm - Variable in class smile.base.mlp.MultilayerPerceptron
The gradient clipping norm.
clipValue - Variable in class smile.base.mlp.MultilayerPerceptron
The gradient clipping value.
clone() - Method in class smile.deep.tensor.Tensor
 
clone() - Method in class smile.math.matrix.BandMatrix
 
clone() - Method in class smile.math.matrix.BigMatrix
Returns a deep copy of matrix.
clone() - Method in class smile.math.matrix.fp32.BandMatrix
 
clone() - Method in class smile.math.matrix.fp32.Matrix
Returns a deep copy of matrix.
clone() - Method in class smile.math.matrix.fp32.SparseMatrix
 
clone() - Method in class smile.math.matrix.fp32.SymmMatrix
 
clone() - Method in class smile.math.matrix.Matrix
Returns a deep copy of matrix.
clone() - Method in class smile.math.matrix.SparseMatrix
 
clone() - Method in class smile.math.matrix.SymmMatrix
 
clone() - Method in class smile.neighbor.lsh.Probe
 
clone(double[][]) - Static method in class smile.math.MathEx
Deep clone a two-dimensional array.
clone(float[][]) - Static method in class smile.math.MathEx
Deep clone a two-dimensional array.
clone(int[][]) - Static method in class smile.math.MathEx
Deep clone a two-dimensional array.
close() - Method in class smile.data.SQL
 
close() - Method in record class smile.deep.SampleBatch
 
close() - Method in class smile.deep.tensor.Tensor
 
close() - Method in class smile.io.Arff
 
close() - Method in class smile.util.AutoScope
 
CLOSING_PARENTHESIS - Enum constant in enum class smile.nlp.pos.PennTreebankPOS
Punctuation ) ] }
CLOSING_QUOTATION - Enum constant in enum class smile.nlp.pos.PennTreebankPOS
Punctuation ' or ''
clustering(double[][], double[][], int[], int[]) - Method in class smile.clustering.BBDTree
Given k cluster centroids, this method assigns data to nearest centroids.
ClusteringMetric - Interface in smile.validation.metric
An abstract interface to measure the clustering performance.
CNB - Enum constant in enum class smile.classification.DiscreteNaiveBayes.Model
Complement Naive Bayes.
coefficients() - Method in class smile.classification.LogisticRegression.Binomial
Returns an array of size (p+1) containing the linear weights of binary logistic regression, where p is the dimension of feature vectors.
coefficients() - Method in class smile.classification.LogisticRegression.Multinomial
Returns a 2d-array of size (k-1) x (p+1), containing the linear weights of multi-class logistic regression, where k is the number of classes and p is the dimension of feature vectors.
coefficients() - Method in class smile.classification.Maxent.Binomial
Returns an array of size (p+1) containing the linear weights of binary logistic regression, where p is the dimension of feature vectors.
coefficients() - Method in class smile.classification.Maxent.Multinomial
Returns a 2d-array of size (k-1) x (p+1), containing the linear weights of multi-class logistic regression, where k is the number of classes and p is the dimension of feature vectors.
coefficients() - Method in class smile.classification.SparseLogisticRegression.Binomial
Returns an array of size (p+1) containing the linear weights of binary logistic regression, where p is the dimension of feature vectors.
coefficients() - Method in class smile.classification.SparseLogisticRegression.Multinomial
Returns a 2d-array of size (k-1) x (p+1), containing the linear weights of multi-class logistic regression, where k is the number of classes and p is the dimension of feature vectors.
coefficients() - Method in class smile.glm.GLM
Returns an array of size (p+1) containing the linear weights of binary logistic regression, where p is the dimension of feature vectors.
coefficients() - Method in class smile.regression.LinearModel
Returns the linear coefficients without intercept.
coerce(DataType, DataType) - Static method in interface smile.data.type.DataType
Returns the common type.
CoifletWavelet - Class in smile.wavelet
Coiflet wavelets.
CoifletWavelet(int) - Constructor for class smile.wavelet.CoifletWavelet
Constructor.
col(int) - Method in class smile.math.matrix.BigMatrix
Returns the j-th column.
col(int) - Method in class smile.math.matrix.fp32.Matrix
Returns the j-th column.
col(int) - Method in class smile.math.matrix.Matrix
Returns the j-th column.
col(int...) - Method in class smile.math.matrix.BigMatrix
Returns the matrix of selected columns.
COL_MAJOR - Enum constant in enum class smile.math.blas.Layout
Column major layout.
collect() - Static method in interface smile.data.DataFrame.Collectors
Returns a stream collector that accumulates tuples into a DataFrame.
collect(Class<T>) - Static method in interface smile.data.DataFrame.Collectors
Returns a stream collector that accumulates objects into a DataFrame.
collector() - Static method in interface smile.data.Dataset
Returns a stream collector that accumulates elements into a Dataset.
collector() - Static method in class smile.math.matrix.Matrix
Returns a stream collector that accumulates elements into a Matrix.
colMax(double[][]) - Static method in class smile.math.MathEx
Returns the column maximum of a matrix.
colMax(int[][]) - Static method in class smile.math.MathEx
Returns the column maximum of a matrix.
colMeans() - Method in class smile.math.matrix.BigMatrix
Returns the mean of each column.
colMeans() - Method in class smile.math.matrix.fp32.Matrix
Returns the mean of each column.
colMeans() - Method in class smile.math.matrix.Matrix
Returns the mean of each column.
colMeans(double[][]) - Static method in class smile.math.MathEx
Returns the column means of a matrix.
colMin(double[][]) - Static method in class smile.math.MathEx
Returns the column minimum of a matrix.
colMin(int[][]) - Static method in class smile.math.MathEx
Returns the column minimum of a matrix.
colName(int) - Method in class smile.math.matrix.fp32.IMatrix
Returns the name of i-th column.
colName(int) - Method in class smile.math.matrix.IMatrix
Returns the name of i-th column.
colNames() - Method in class smile.math.matrix.fp32.IMatrix
Returns the column names.
colNames() - Method in class smile.math.matrix.IMatrix
Returns the column names.
colNames(String[]) - Method in class smile.math.matrix.fp32.IMatrix
Sets the column names.
colNames(String[]) - Method in class smile.math.matrix.IMatrix
Sets the column names.
Colon - Static variable in class smile.deep.tensor.Index
The colon (:) is used to slice all elements of a dimension.
COLON - Enum constant in enum class smile.nlp.pos.PennTreebankPOS
Punctuation ; : ...
color(String) - Method in class smile.plot.vega.Mark
Sets the default color.
ColorCellEditor - Class in smile.swing.table
Color editor in JTable.
ColorCellEditor() - Constructor for class smile.swing.table.ColorCellEditor
Constructor.
ColorCellRenderer - Class in smile.swing.table
Color renderer in JTable.
ColorCellRenderer() - Constructor for class smile.swing.table.ColorCellRenderer
Constructor.
ColorCellRenderer(boolean) - Constructor for class smile.swing.table.ColorCellRenderer
Constructor.
COLORS - Static variable in interface smile.plot.swing.Palette
 
cols(int...) - Method in class smile.math.matrix.fp32.Matrix
Returns the matrix of selected columns.
cols(int...) - Method in class smile.math.matrix.Matrix
Returns the matrix of selected columns.
colSds() - Method in class smile.math.matrix.BigMatrix
Returns the standard deviations of each column.
colSds() - Method in class smile.math.matrix.fp32.Matrix
Returns the standard deviations of each column.
colSds() - Method in class smile.math.matrix.Matrix
Returns the standard deviations of each column.
colSds(double[][]) - Static method in class smile.math.MathEx
Returns the column standard deviations of a matrix.
colSums() - Method in class smile.math.matrix.BigMatrix
Returns the sum of each column.
colSums() - Method in class smile.math.matrix.fp32.Matrix
Returns the sum of each column.
colSums() - Method in class smile.math.matrix.Matrix
Returns the sum of each column.
colSums(double[][]) - Static method in class smile.math.MathEx
Returns the column sums of a matrix.
colSums(int[][]) - Static method in class smile.math.MathEx
Returns the column sums of a matrix.
column(double[]) - Static method in class smile.math.matrix.BigMatrix
Returns a column vector/matrix.
column(double[]) - Static method in class smile.math.matrix.fp32.Matrix
Returns a column vector/matrix.
column(double[]) - Static method in class smile.math.matrix.Matrix
Returns a column vector/matrix.
column(double[], int, int) - Static method in class smile.math.matrix.BigMatrix
Returns a column vector/matrix.
column(double[], int, int) - Static method in class smile.math.matrix.fp32.Matrix
Returns a column vector/matrix.
column(double[], int, int) - Static method in class smile.math.matrix.Matrix
Returns a column vector/matrix.
column(float[]) - Static method in class smile.math.matrix.fp32.Matrix
Returns a column vector/matrix.
column(float[], int, int) - Static method in class smile.math.matrix.fp32.Matrix
Returns a column vector/matrix.
column(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
column(int) - Method in class smile.data.IndexDataFrame
 
column(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
column(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
column(String) - Method in class smile.plot.vega.Facet
Returns the field definition for the vertical facet of trellis plots.
columnAdded(TableColumnModelEvent) - Method in class smile.swing.table.TableColumnSettings
 
columnMarginChanged(ChangeEvent) - Method in class smile.swing.table.TableColumnSettings
 
columnMoved(TableColumnModelEvent) - Method in class smile.swing.table.TableColumnSettings
 
columnPadding(double) - Method in class smile.plot.vega.Legend
Sets the horizontal padding in pixels between symbol legend entries.
columnRemoved(TableColumnModelEvent) - Method in class smile.swing.table.TableColumnSettings
 
columns - Variable in class smile.feature.extraction.Projection
The fields of input space.
columns(int) - Method in class smile.plot.vega.Facet
Sets the number of columns to include in the view composition layout.
columns(int) - Method in class smile.plot.vega.Legend
Sets the number of columns in which to arrange symbol legend entries.
columns(int) - Method in class smile.plot.vega.Repeat
Sets the number of columns to include in the view composition layout.
columnSelectionChanged(ListSelectionEvent) - Method in class smile.swing.table.TableColumnSettings
 
ColumnTransform - Class in smile.data.transform
Column-wise data transformation.
ColumnTransform(String, Map<String, Function>) - Constructor for class smile.data.transform.ColumnTransform
Constructor.
COMMA - Enum constant in enum class smile.nlp.pos.PennTreebankPOS
Punctuation ,
COMPACT - Enum constant in enum class smile.math.blas.SVDJob
The first min(m, n) singular vectors are returned in supplied matrix U (or Vt).
comparator - Static variable in class smile.base.cart.Split
The comparator on the split score.
compareTo(CentroidClustering<T, U>) - Method in class smile.clustering.CentroidClustering
 
compareTo(MEC<T>) - Method in class smile.clustering.MEC
 
compareTo(InformationValue) - Method in class smile.feature.selection.InformationValue
 
compareTo(SignalNoiseRatio) - Method in class smile.feature.selection.SignalNoiseRatio
 
compareTo(SumSquaresRatio) - Method in class smile.feature.selection.SumSquaresRatio
 
compareTo(Chromosome) - Method in class smile.gap.BitString
 
compareTo(PrH) - Method in class smile.neighbor.lsh.PrH
 
compareTo(Probe) - Method in class smile.neighbor.lsh.Probe
 
compareTo(PrZ) - Method in class smile.neighbor.lsh.PrZ
 
compareTo(Neighbor<K, V>) - Method in class smile.neighbor.Neighbor
 
compareTo(Bigram) - Method in class smile.nlp.collocation.Bigram
 
compareTo(NGram) - Method in class smile.nlp.collocation.NGram
 
compareTo(Relevance) - Method in class smile.nlp.relevance.Relevance
 
compareTo(Neuron) - Method in class smile.vq.hebb.Neuron
 
CompleteLinkage - Class in smile.clustering.linkage
Complete linkage.
CompleteLinkage(double[][]) - Constructor for class smile.clustering.linkage.CompleteLinkage
Constructor.
CompleteLinkage(int, float[]) - Constructor for class smile.clustering.linkage.CompleteLinkage
Constructor.
Complex - Class in smile.math
Complex number.
Complex(double, double) - Constructor for class smile.math.Complex
Constructor.
Complex.Array - Class in smile.math
Packed array of complex numbers for better memory efficiency.
Component(double, DiscreteDistribution) - Constructor for class smile.stat.distribution.DiscreteMixture.Component
Constructor.
Component(double, Distribution) - Constructor for class smile.stat.distribution.Mixture.Component
Constructor.
Component(double, MultivariateDistribution) - Constructor for class smile.stat.distribution.MultivariateMixture.Component
Constructor.
components - Variable in class smile.ica.ICA
The independent components (row-wise).
components - Variable in class smile.stat.distribution.DiscreteMixture
The components of finite mixture model.
components - Variable in class smile.stat.distribution.Mixture
The components of finite mixture model.
components - Variable in class smile.stat.distribution.MultivariateMixture
The components of finite mixture model.
compose(Transform) - Method in interface smile.data.transform.Transform
Returns a composed function that first applies the before function to its input, and then applies this function to the result.
COMPREHENSIVE - Enum constant in enum class smile.nlp.dictionary.EnglishStopWords
A very long list of stop words.
compute() - Method in class smile.deep.metric.Accuracy
 
compute() - Method in interface smile.deep.metric.Metric
Computes the metric value from the metric state, which are updated by previous update() calls.
compute() - Method in class smile.deep.metric.Precision
 
compute() - Method in class smile.deep.metric.Recall
 
computeGradient(double[]) - Method in class smile.base.mlp.InputLayer
 
computeGradient(double[]) - Method in class smile.base.mlp.Layer
Computes the parameter gradient for a sample of (mini-)batch.
computeGradientUpdate(double[], double, double, double) - Method in class smile.base.mlp.InputLayer
 
computeGradientUpdate(double[], double, double, double) - Method in class smile.base.mlp.Layer
Computes the parameter gradient and update the weights.
computeOutputGradient(double[], double) - Method in class smile.base.mlp.OutputLayer
Compute the network output gradient.
Concat - Class in smile.plot.vega
Concatenating views.
Concat(int, VegaLite...) - Constructor for class smile.plot.vega.Concat
Constructor to put multiple views into a flexible flow layout.
Concept - Class in smile.taxonomy
Concept is a set of synonyms, i.e.
Concept(Concept, String...) - Constructor for class smile.taxonomy.Concept
Constructor.
CONCISE - Enum constant in enum class smile.nlp.dictionary.EnglishDictionary
A concise dictionary of common terms in English.
condition() - Method in class smile.math.matrix.BigMatrix.SVD
Returns the L2 norm condition number, which is max(S) / min(S).
condition() - Method in class smile.math.matrix.fp32.Matrix.SVD
Returns the L2 norm condition number, which is max(S) / min(S).
condition() - Method in class smile.math.matrix.Matrix.SVD
Returns the L2 norm condition number, which is max(S) / min(S).
confidence - Variable in class smile.association.AssociationRule
The confidence value.
config() - Method in class smile.plot.vega.VegaLite
Returns the configuration object that lists properties of a visualization for creating a consistent theme.
Config - Class in smile.plot.vega
Vega-Lite's config object lists configuration properties of a visualization for creating a consistent theme.
confusion - Variable in class smile.validation.ClassificationValidation
The confusion matrix.
ConfusionMatrix - Class in smile.validation.metric
The confusion matrix of truth and predictions.
ConfusionMatrix(int[][]) - Constructor for class smile.validation.metric.ConfusionMatrix
Constructor.
conjugate() - Method in class smile.math.Complex
Returns the conjugate.
CONJUGATE_TRANSPOSE - Enum constant in enum class smile.math.blas.Transpose
Conjugate transpose operation on the matrix.
consequent - Variable in class smile.association.AssociationRule
Consequent itemset.
constant(double) - Static method in interface smile.math.TimeFunction
Returns the constant learning rate.
Constant - Class in smile.data.formula
A constant value in the formula.
Constant() - Constructor for class smile.data.formula.Constant
 
contains(double[][], double[]) - Static method in class smile.math.MathEx
Determines if the polygon contains the point.
contains(double[][], double, double) - Static method in class smile.math.MathEx
Determines if the polygon contains the point.
contains(int) - Method in class smile.util.IntHashSet
Returns true if this set contains the specified element.
contains(String) - Method in interface smile.nlp.dictionary.Dictionary
Returns true if this dictionary contains the specified word.
contains(String) - Method in enum class smile.nlp.dictionary.EnglishDictionary
 
contains(String) - Method in class smile.nlp.dictionary.EnglishPunctuations
 
contains(String) - Method in enum class smile.nlp.dictionary.EnglishStopWords
 
contains(String) - Method in class smile.nlp.dictionary.SimpleDictionary
 
content() - Method in record class smile.llm.llama.Message
Returns the value of the content record component.
ContingencyTable - Class in smile.validation.metric
The contingency table.
ContingencyTable(int[], int[]) - Constructor for class smile.validation.metric.ContingencyTable
Constructor.
continuousHeight(int) - Method in class smile.plot.vega.ViewConfig
Sets the default height when the plot has a continuous field for y or latitude, or has arc marks.
continuousWidth(int) - Method in class smile.plot.vega.ViewConfig
Sets the default width when the plot has a continuous field for x or longitude, or has arc marks.
Contour - Class in smile.plot.swing
A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format.
Contour(double[][], double[]) - Constructor for class smile.plot.swing.Contour
Constructor.
Contour(double[][], int, boolean) - Constructor for class smile.plot.swing.Contour
Constructor.
Contour(double[], double[], double[][], double[]) - Constructor for class smile.plot.swing.Contour
Constructor.
Contour(double[], double[], double[][], int, boolean) - Constructor for class smile.plot.swing.Contour
Constructor.
conv2d(int, int, int) - Static method in interface smile.deep.layer.Layer
Returns a convolutional layer.
conv2d(int, int, int, int, int, int, int, boolean, String) - Static method in interface smile.deep.layer.Layer
Returns a convolutional layer.
conv2d(int, int, int, int, String, int, int, boolean, String) - Static method in interface smile.deep.layer.Layer
Returns a convolutional layer.
Conv2dLayer - Class in smile.deep.layer
A convolutional layer.
Conv2dLayer(int, int, int, int, int, int, int, boolean, String) - Constructor for class smile.deep.layer.Conv2dLayer
Constructor.
Conv2dLayer(int, int, int, int, String, int, int, boolean, String) - Constructor for class smile.deep.layer.Conv2dLayer
Constructor.
Conv2dNormActivation - Class in smile.vision.layer
Convolution2d-Normalization-Activation block.
Conv2dNormActivation(Conv2dNormActivation.Options) - Constructor for class smile.vision.layer.Conv2dNormActivation
Constructor.
Conv2dNormActivation.Options - Record Class in smile.vision.layer
Conv2dNormActivation configurations.
CooccurrenceKeywords - Interface in smile.nlp.keyword
Keyword extraction from a single document using word co-occurrence statistical information.
coordinates - Variable in class smile.manifold.IsoMap
The coordinate matrix in embedding space.
coordinates - Variable in class smile.manifold.IsotonicMDS
The coordinates.
coordinates - Variable in class smile.manifold.LaplacianEigenmap
The coordinate matrix in embedding space.
coordinates - Variable in class smile.manifold.LLE
The coordinate matrix in embedding space.
coordinates - Variable in class smile.manifold.MDS
The principal coordinates.
coordinates - Variable in class smile.manifold.SammonMapping
The coordinates.
coordinates - Variable in class smile.manifold.TSNE
The coordinate matrix in embedding space.
coordinates - Variable in class smile.manifold.UMAP
The coordinate matrix in embedding space.
coordinates() - Method in class smile.manifold.KPCA
Returns the nonlinear principal component scores, i.e., the representation of learning data in the nonlinear principal component space.
copy(double[][], double[][]) - Static method in class smile.math.MathEx
Deep copy x into y.
copy(float[][], float[][]) - Static method in class smile.math.MathEx
Deep copy x into y.
copy(int[][], int[][]) - Static method in class smile.math.MathEx
Copy x into y.
cor - Variable in class smile.stat.hypothesis.CorTest
The correlation coefficient.
cor(double[][]) - Static method in class smile.math.MathEx
Returns the sample correlation matrix.
cor(double[][], double[]) - Static method in class smile.math.MathEx
Returns the sample correlation matrix.
cor(double[][], String...) - Static method in class smile.feature.extraction.PCA
Fits principal component analysis with correlation matrix.
cor(double[], double[]) - Static method in class smile.math.MathEx
Returns the correlation coefficient between two vectors.
cor(float[], float[]) - Static method in class smile.math.MathEx
Returns the correlation coefficient between two vectors.
cor(int[], int[]) - Static method in class smile.math.MathEx
Returns the correlation coefficient between two vectors.
cor(DataFrame, String...) - Static method in class smile.feature.extraction.PCA
Fits principal component analysis with correlation matrix.
cornerRadius(double) - Method in class smile.plot.vega.Legend
Sets the corner radius for the full legend.
cornerRadius(double) - Method in class smile.plot.vega.Mark
Sets the radius in pixels of rounded rectangles or arcs' corners.
cornerRadius(int) - Method in class smile.plot.vega.Background
Sets the radius of corners.
cornerRadius(int) - Method in class smile.plot.vega.ViewConfig
Sets the radius of corners.
cornerRadiusBottomLeft(double) - Method in class smile.plot.vega.Mark
Sets the radius in pixels of rounded rectangles' bottom left corner.
cornerRadiusBottomRight(double) - Method in class smile.plot.vega.Mark
Sets the radius in pixels of rounded rectangles' bottom right corner.
cornerRadiusEnd(double) - Method in class smile.plot.vega.Mark
For vertical bars, sets the top-left and top-right corner radius.
cornerRadiusTopLeft(double) - Method in class smile.plot.vega.Mark
Sets the radius in pixels of rounded rectangles' top left corner.
cornerRadiusTopRight(double) - Method in class smile.plot.vega.Mark
Sets the radius in pixels of rounded rectangles' top right corner.
Corpus - Interface in smile.nlp
A corpus is a collection of documents.
CorrelationDistance - Class in smile.math.distance
Correlation distance is defined as 1 - correlation coefficient.
CorrelationDistance() - Constructor for class smile.math.distance.CorrelationDistance
Constructor of Pearson correlation distance.
CorrelationDistance(String) - Constructor for class smile.math.distance.CorrelationDistance
Constructor.
CorTest - Class in smile.stat.hypothesis
Correlation test.
CorTest(String, double, double, double, double) - Constructor for class smile.stat.hypothesis.CorTest
Constructor.
cos() - Method in class smile.deep.tensor.Tensor
Returns a new tensor with the cosine of the elements of input.
cos() - Method in class smile.math.Complex
Returns the complex cosine.
cos(double[], double[]) - Static method in class smile.math.MathEx
Returns the cosine similarity.
cos(float[], float[]) - Static method in class smile.math.MathEx
Returns the cosine similarity.
cos(String) - Static method in interface smile.data.formula.Terms
The cos(x) term.
cos(Term) - Static method in interface smile.data.formula.Terms
The cos(x) term.
cos_() - Method in class smile.deep.tensor.Tensor
Computes the cosine of the elements of input in place.
cosh(String) - Static method in interface smile.data.formula.Terms
The cosh(x) term.
cosh(Term) - Static method in interface smile.data.formula.Terms
The cosh(x) term.
cosine(double, double, double) - Static method in interface smile.math.TimeFunction
Returns the cosine annealing function.
cost() - Method in class smile.base.mlp.OutputLayer
Returns the cost function of neural network.
cost() - Method in class smile.manifold.TSNE
Returns the cost function value.
Cost - Enum Class in smile.base.mlp
Neural network cost function.
count - Variable in class smile.nlp.collocation.Bigram
The frequency of bigram in the corpus.
count - Variable in class smile.nlp.collocation.NGram
The frequency of n-gram in the corpus.
count() - Method in class smile.base.cart.DecisionNode
Returns the number of node samples in each class.
count(String) - Method in interface smile.nlp.Corpus
Returns the total frequency of the term in the corpus.
count(String) - Method in class smile.nlp.SimpleCorpus
 
count(Bigram) - Method in interface smile.nlp.Corpus
Returns the total frequency of the bigram in the corpus.
count(Bigram) - Method in class smile.nlp.SimpleCorpus
 
counter - Variable in class smile.vq.hebb.Neuron
The local counter variable (e.g.
counts(boolean) - Method in class smile.plot.vega.DensityTransform
Produces probability estimates or smoothed counts.
countTitle(String) - Method in class smile.plot.vega.Config
Sets the default axis and legend title for count fields.
cov - Variable in class smile.regression.GaussianProcessRegression.JointPrediction
The covariance matrix of joint predictive distribution at query points.
cov() - Method in interface smile.stat.distribution.MultivariateDistribution
The covariance matrix of distribution.
cov() - Method in class smile.stat.distribution.MultivariateGaussianDistribution
 
cov() - Method in class smile.stat.distribution.MultivariateMixture
 
cov(double[][]) - Static method in class smile.math.MathEx
Returns the sample covariance matrix.
cov(double[][], double[]) - Static method in class smile.math.MathEx
Returns the sample covariance matrix.
cov(double[], double[]) - Static method in class smile.math.MathEx
Returns the covariance between two vectors.
cov(double[], int) - Static method in interface smile.timeseries.TimeSeries
Autocovariance function.
cov(float[], float[]) - Static method in class smile.math.MathEx
Returns the covariance between two vectors.
cov(int[], int[]) - Static method in class smile.math.MathEx
Returns the covariance between two vectors.
CoverTree<K,V> - Class in smile.neighbor
Cover tree is a data structure for generic nearest neighbor search, which is especially efficient in spaces with small intrinsic dimension.
CoverTree(List<K>, List<V>, Metric<K>) - Constructor for class smile.neighbor.CoverTree
Constructor.
CoverTree(List<K>, List<V>, Metric<K>, double) - Constructor for class smile.neighbor.CoverTree
Constructor.
CoverTree(K[], V[], Metric<K>) - Constructor for class smile.neighbor.CoverTree
Constructor.
CoverTree(K[], V[], Metric<K>, double) - Constructor for class smile.neighbor.CoverTree
Constructor.
CPU - Enum constant in enum class smile.deep.tensor.DeviceType
CPU
CPU() - Static method in class smile.deep.tensor.Device
Returns the CPU device.
CramerV - Variable in class smile.stat.hypothesis.ChiSqTest
Cramér's V is a measure of association between two nominal variables, giving a value between 0 and 1 (inclusive).
CRF - Class in smile.sequence
First-order linear conditional random field.
CRF(StructType, RegressionTree[][], double) - Constructor for class smile.sequence.CRF
Constructor.
CRFLabeler<T> - Class in smile.sequence
First-order CRF sequence labeler.
CRFLabeler(CRF, Function<T, Tuple>) - Constructor for class smile.sequence.CRFLabeler
Constructor.
crop(BufferedImage, int, boolean) - Method in interface smile.vision.transform.Transform
Crops an image.
crop(BufferedImage, int, int, boolean) - Method in interface smile.vision.transform.Transform
Crops an image.
cross(int, String...) - Static method in interface smile.data.formula.Terms
Factor crossing of two or more factors.
cross(String...) - Static method in interface smile.data.formula.Terms
Factor crossing of two or more factors.
crossentropy - Variable in class smile.validation.ClassificationMetrics
The cross entropy on validation data.
crossEntropy() - Static method in interface smile.deep.Loss
Cross Entropy Loss Function.
CrossEntropy - Interface in smile.validation.metric
Cross entropy generalizes the log loss metric to multiclass problems.
crossover(Chromosome) - Method in class smile.gap.BitString
 
crossover(Chromosome) - Method in interface smile.gap.Chromosome
Returns a pair of offsprings by crossovering this one with another one according to the crossover rate, which determines how often will be crossover performed.
Crossover - Enum Class in smile.gap
The types of crossover operation.
CrossValidation - Interface in smile.validation
Cross-validation is a technique for assessing how the results of a statistical analysis will generalize to an independent data set.
csv(String) - Static method in interface smile.io.Read
Reads a CSV file.
csv(String, char, Map<String, String>, String...) - Method in class smile.data.SQL
Creates an in-memory table from csv files.
csv(String, String) - Static method in interface smile.io.Read
Reads a CSV file.
csv(String, String...) - Method in class smile.data.SQL
Creates an in-memory table from csv files.
csv(String, Map<String, String>) - Method in class smile.plot.vega.Data
Loads a comma-separated values (CSV) file
csv(String, CSVFormat) - Static method in interface smile.io.Read
Reads a CSV file.
csv(String, CSVFormat, StructType) - Static method in interface smile.io.Read
Reads a CSV file.
csv(Path) - Static method in interface smile.io.Read
Reads a CSV file.
csv(Path, CSVFormat) - Static method in interface smile.io.Read
Reads a CSV file.
csv(Path, CSVFormat, StructType) - Static method in interface smile.io.Read
Reads a CSV file.
csv(DataFrame, Path) - Static method in interface smile.io.Write
Writes a CSV file.
csv(DataFrame, Path, CSVFormat) - Static method in interface smile.io.Write
Writes a CSV file.
CSV - Class in smile.io
Reads and writes files in variations of the Comma Separated Value (CSV) format.
CSV() - Constructor for class smile.io.CSV
Constructor.
CSV(CSVFormat) - Constructor for class smile.io.CSV
Constructor.
CubicSplineInterpolation1D - Class in smile.interpolation
Cubic spline interpolation.
CubicSplineInterpolation1D(double[], double[]) - Constructor for class smile.interpolation.CubicSplineInterpolation1D
Constructor.
CubicSplineInterpolation2D - Class in smile.interpolation
Cubic spline interpolation in a two-dimensional regular grid.
CubicSplineInterpolation2D(double[], double[], double[][]) - Constructor for class smile.interpolation.CubicSplineInterpolation2D
Constructor.
CUDA - Enum constant in enum class smile.deep.tensor.DeviceType
NVIDIA GPU
CUDA - Interface in smile.deep
NVIDIA CUDA helper functions.
CUDA() - Static method in class smile.deep.tensor.Device
Returns the default NVIDIA CUDA device.
CUDA(byte) - Static method in class smile.deep.tensor.Device
Returns the NVIDIA CUDA device.
cumulative(boolean) - Method in class smile.plot.vega.DensityTransform
Produces density estimates or cumulative density estimates.
cumulativeVarianceProportion() - Method in class smile.feature.extraction.PCA
Returns the cumulative proportion of variance contained in principal components, ordered from largest to smallest.
Currency - Static variable in interface smile.data.measure.Measure
Currency.
CURRENCY - Static variable in class smile.swing.table.NumberCellRenderer
 
cursor(String) - Method in class smile.plot.vega.Background
Sets the mouse cursor used over the view.
cursor(String) - Method in class smile.plot.vega.ViewConfig
Sets the mouse cursor used over the view.
customFormatTypes(boolean) - Method in class smile.plot.vega.FormatConfig
Allow the formatType property for text marks and guides to accept a custom formatter function registered as a Vega expression.
CYAN - Static variable in interface smile.plot.swing.Palette
 

D

d - Variable in class smile.stat.hypothesis.KSTest
Kolmogorov-Smirnov statistic.
d - Variable in class smile.vq.BIRCH
The dimensionality of data.
d(byte[], byte[]) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two byte arrays.
d(byte, byte) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two bytes.
d(char[], char[]) - Method in class smile.math.distance.EditDistance
Edit distance between two strings.
d(double[], double[]) - Method in class smile.math.distance.ChebyshevDistance
Chebyshev distance between the two arrays of type double.
d(double[], double[]) - Method in class smile.math.distance.CorrelationDistance
Pearson correlation distance between the two arrays of type double.
d(double[], double[]) - Static method in class smile.math.distance.DynamicTimeWarping
Dynamic time warping without path constraints.
d(double[], double[]) - Method in class smile.math.distance.EuclideanDistance
Euclidean distance between the two arrays of type double.
d(double[], double[]) - Method in class smile.math.distance.JensenShannonDistance
 
d(double[], double[]) - Method in class smile.math.distance.MahalanobisDistance
 
d(double[], double[]) - Method in class smile.math.distance.ManhattanDistance
Manhattan distance between two arrays of type double.
d(double[], double[]) - Method in class smile.math.distance.MinkowskiDistance
Minkowski distance between the two arrays of type double.
d(double[], double[], int) - Static method in class smile.math.distance.DynamicTimeWarping
Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.
d(float[], float[]) - Static method in class smile.math.distance.ChebyshevDistance
Chebyshev distance between the two arrays of type float.
d(float[], float[]) - Static method in class smile.math.distance.DynamicTimeWarping
Dynamic time warping without path constraints.
d(float[], float[]) - Method in class smile.math.distance.EuclideanDistance
Euclidean distance between the two arrays of type float.
d(float[], float[]) - Method in class smile.math.distance.ManhattanDistance
Manhattan distance between two arrays of type float.
d(float[], float[]) - Method in class smile.math.distance.MinkowskiDistance
Minkowski distance between the two arrays of type float.
d(float[], float[], int) - Static method in class smile.math.distance.DynamicTimeWarping
Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.
d(int[], int[]) - Static method in class smile.math.distance.ChebyshevDistance
Chebyshev distance between the two arrays of type integer.
d(int[], int[]) - Static method in class smile.math.distance.DynamicTimeWarping
Dynamic time warping without path constraints.
d(int[], int[]) - Method in class smile.math.distance.EuclideanDistance
Euclidean distance between the two arrays of type integer.
d(int[], int[]) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two integer arrays.
d(int[], int[]) - Method in class smile.math.distance.LeeDistance
 
d(int[], int[]) - Method in class smile.math.distance.ManhattanDistance
Manhattan distance between two arrays of type integer.
d(int[], int[]) - Method in class smile.math.distance.MinkowskiDistance
Minkowski distance between the two arrays of type integer.
d(int[], int[], int) - Static method in class smile.math.distance.DynamicTimeWarping
Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.
d(int, int) - Method in class smile.clustering.linkage.Linkage
Returns the distance/dissimilarity between two clusters/objects, which are indexed by integers.
d(int, int) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two integers.
d(long, long) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two long integers.
d(short[], short[]) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two short arrays.
d(short, short) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two shorts.
d(String, String) - Method in class smile.math.distance.EditDistance
Edit distance between two strings.
d(String, String) - Method in class smile.taxonomy.TaxonomicDistance
Computes the distance between two concepts in a taxonomy.
d(BitSet, BitSet) - Method in class smile.math.distance.HammingDistance
 
d(Set<T>, Set<T>) - Static method in class smile.math.distance.JaccardDistance
Returns the Jaccard distance between sets.
d(Concept, Concept) - Method in class smile.taxonomy.TaxonomicDistance
Computes the distance between two concepts in a taxonomy.
d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseChebyshevDistance
 
d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseEuclideanDistance
 
d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseManhattanDistance
 
d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseMinkowskiDistance
 
d(T[], T[]) - Method in class smile.math.distance.DynamicTimeWarping
 
d(T[], T[]) - Method in class smile.math.distance.JaccardDistance
 
d(T, T) - Method in interface smile.math.distance.Distance
Returns the distance measure between two objects.
D(T[]) - Method in interface smile.math.distance.Distance
Returns the pairwise distance matrix.
D(T[], T[]) - Method in interface smile.math.distance.Distance
Returns the pairwise distance matrix.
D4Wavelet - Class in smile.wavelet
The simplest and most localized wavelet, Daubechies wavelet of 4 coefficients.
D4Wavelet() - Constructor for class smile.wavelet.D4Wavelet
Constructor.
damerau(char[], char[]) - Static method in class smile.math.distance.EditDistance
Damerau-Levenshtein distance between two strings allows insertion, deletion, substitution, or transposition of characters.
damerau(String, String) - Static method in class smile.math.distance.EditDistance
Damerau-Levenshtein distance between two strings allows insertion, deletion, substitution, or transposition of characters.
DARK_BLUE - Static variable in interface smile.plot.swing.Palette
 
DARK_CYAN - Static variable in interface smile.plot.swing.Palette
 
DARK_GRAY - Static variable in interface smile.plot.swing.Palette
 
DARK_GREEN - Static variable in interface smile.plot.swing.Palette
 
DARK_MAGENTA - Static variable in interface smile.plot.swing.Palette
 
DARK_PURPLE - Static variable in interface smile.plot.swing.Palette
 
DARK_RED - Static variable in interface smile.plot.swing.Palette
 
DARK_SLATE_GRAY - Static variable in interface smile.plot.swing.Palette
 
DASH - Enum constant in enum class smile.nlp.pos.PennTreebankPOS
Punctuation -
DASH - Enum constant in enum class smile.plot.swing.Line.Style
 
data - Variable in class smile.neighbor.LSH
The data objects.
data() - Method in record class smile.deep.SampleBatch
Returns the value of the data record component.
data() - Method in class smile.plot.vega.LookupData
Returns the secondary data source.
data() - Method in class smile.plot.vega.VegaLite
Returns the data specification object.
data(String) - Static method in interface smile.io.Read
Reads a data file.
data(String, String) - Static method in interface smile.io.Read
Reads a data file.
Data - Class in smile.plot.vega
The basic data model used by Vega-Lite is tabular data.
DataFrame - Interface in smile.data
An immutable collection of data organized into named columns.
DataFrame.Collectors - Interface in smile.data
Stream collectors.
DataFrameClassifier - Interface in smile.classification
Classification trait on DataFrame.
DataFrameClassifier.Trainer<M> - Interface in smile.classification
The classifier trainer.
DataFrameRegression - Interface in smile.regression
Regression trait on DataFrame.
DataFrameRegression.Trainer<M> - Interface in smile.regression
The regression trainer.
Dataset<D,T> - Interface in smile.data
An immutable collection of data objects.
Dataset - Interface in smile.deep
A dataset consists of data and an associated target (label) and can be iterated in mini-batches.
DataType - Interface in smile.data.type
The interface of data types.
DataType.ID - Enum Class in smile.data.type
Data type ID.
DataTypes - Class in smile.data.type
To get a specific data type, users should use singleton objects and factory methods in this class.
DataTypes() - Constructor for class smile.data.type.DataTypes
 
date(String) - Static method in class smile.data.type.DataTypes
Date data type with customized format.
date(String, DateFeature...) - Static method in interface smile.data.formula.Terms
Extracts date/time features.
Date - Class in smile.data.formula
Date/time feature extractor.
Date - Enum constant in enum class smile.data.type.DataType.ID
Date type ID.
Date(String, DateFeature...) - Constructor for class smile.data.formula.Date
Constructor.
DATE - Static variable in interface smile.util.Regex
Date regular expression pattern.
DateCellEditor - Class in smile.swing.table
Implements a cell editor that uses a formatted text field to edit Date values.
DateCellEditor(String) - Constructor for class smile.swing.table.DateCellEditor
Constructor.
DateCellEditor(DateFormat) - Constructor for class smile.swing.table.DateCellEditor
Constructor.
DateCellRenderer - Class in smile.swing.table
Date cell renderer.
DateCellRenderer(String) - Constructor for class smile.swing.table.DateCellRenderer
 
DateCellRenderer(DateFormat) - Constructor for class smile.swing.table.DateCellRenderer
 
DateFeature - Enum Class in smile.data.formula
The date/time features.
datetime(String) - Static method in class smile.data.type.DataTypes
DateTime data type with customized format.
DateTime - Enum constant in enum class smile.data.type.DataType.ID
DateTime type ID.
DATETIME - Static variable in interface smile.util.Regex
Datetime regular expression pattern.
DateTimeType - Class in smile.data.type
DateTime data type.
DateTimeType - Static variable in class smile.data.type.DataTypes
DateTime data type with ISO format.
DateTimeType(String) - Constructor for class smile.data.type.DateTimeType
Constructor.
DateType - Class in smile.data.type
Date data type.
DateType - Static variable in class smile.data.type.DataTypes
Date data type with ISO format.
DateType(String) - Constructor for class smile.data.type.DateType
Constructor.
DaubechiesWavelet - Class in smile.wavelet
Daubechies wavelets.
DaubechiesWavelet(int) - Constructor for class smile.wavelet.DaubechiesWavelet
Constructor.
DAY_OF_MONTH - Enum constant in enum class smile.data.formula.DateFeature
The day of month represented by an integer from 1 to 31 in the usual manner.
DAY_OF_WEEK - Enum constant in enum class smile.data.formula.DateFeature
The day of week represented by an integer from 1 to 7; 1 is Monday, 2 is Tuesday, and so forth; thus 7 is Sunday.
DAY_OF_YEAR - Enum constant in enum class smile.data.formula.DateFeature
The day of year represented by an integer from 1 to 365, or 366 in a leap year.
DBSCAN<T> - Class in smile.clustering
Density-Based Spatial Clustering of Applications with Noise.
DBSCAN(int, double, RNNSearch<T, T>, int, int[], boolean[]) - Constructor for class smile.clustering.DBSCAN
Constructor.
Decimal - Enum constant in enum class smile.data.type.DataType.ID
Decimal type ID.
DECIMAL_FORMAT - Static variable in interface smile.util.Strings
Decimal format for floating numbers.
DecimalType - Class in smile.data.type
Arbitrary-precision decimal data type.
DecimalType - Static variable in class smile.data.type.DataTypes
Decimal data type.
DecisionNode - Class in smile.base.cart
A leaf node in decision tree.
DecisionNode(int[]) - Constructor for class smile.base.cart.DecisionNode
Constructor.
DecisionTree - Class in smile.classification
Decision tree.
DecisionTree(DataFrame, int[], StructField, int, SplitRule, int, int, int, int, int[], int[][]) - Constructor for class smile.classification.DecisionTree
Constructor.
decode(int[]) - Method in class smile.llm.tokenizer.SentencePiece
 
decode(int[]) - Method in class smile.llm.tokenizer.Tiktoken
 
decode(int[]) - Method in interface smile.llm.tokenizer.Tokenizer
Decodes a list of token IDs into a string.
decrement() - Method in class smile.util.MutableInt
Decrement by one.
decrement(int) - Method in class smile.util.MutableInt
Decrement.
DEFAULT - Enum constant in enum class smile.nlp.dictionary.EnglishStopWords
Default stop words list.
DEFAULT_MEAN - Static variable in interface smile.vision.transform.Transform
The default mean value of pixel RGB after normalized to [0, 1].
DEFAULT_STD - Static variable in interface smile.vision.transform.Transform
The default standard deviation of pixel RGB after normalized to [0, 1].
DefaultTableHeaderCellRenderer - Class in smile.swing.table
A default cell renderer for a JTableHeader.
DefaultTableHeaderCellRenderer() - Constructor for class smile.swing.table.DefaultTableHeaderCellRenderer
Constructs a DefaultTableHeaderCellRenderer.
degree() - Method in class smile.math.kernel.Polynomial
Returns the degree of polynomial.
delete(String) - Static method in interface smile.data.formula.Terms
Deletes a variable or the intercept ("1") from the formula.
delete(Term) - Static method in interface smile.data.formula.Terms
Deletes a term from the formula.
DENCLUE - Class in smile.clustering
DENsity CLUstering.
DENCLUE(int, double[][], double[], double[][], double, int[], double) - Constructor for class smile.clustering.DENCLUE
Constructor.
Dendrogram - Class in smile.plot.swing
A dendrogram is a tree diagram frequently used to illustrate the arrangement of the clusters produced by hierarchical clustering.
Dendrogram(int[][], double[]) - Constructor for class smile.plot.swing.Dendrogram
Constructor.
Dendrogram(int[][], double[], Color) - Constructor for class smile.plot.swing.Dendrogram
Constructor.
denoise(double[], Wavelet) - Static method in interface smile.wavelet.WaveletShrinkage
Adaptive hard-thresholding denoising a time series with given wavelet.
denoise(double[], Wavelet, boolean) - Static method in interface smile.wavelet.WaveletShrinkage
Adaptive denoising a time series with given wavelet.
density(String, String...) - Method in class smile.plot.vega.Transform
Adds a density transformation.
DensityTransform - Class in smile.plot.vega
The density transform performs one-dimensional kernel density estimation over an input data stream and generates a new data stream of samples of the estimated densities.
depth() - Method in class smile.base.cart.InternalNode
 
depth() - Method in class smile.base.cart.LeafNode
 
depth() - Method in interface smile.base.cart.Node
Returns the maximum depth of the tree -- the number of nodes along the longest path from this node down to the farthest leaf node.
describe(String) - Method in class smile.data.SQL
Returns the columns in a table.
description(String) - Method in class smile.plot.vega.Axis
Sets the text description of this axis for ARIA accessibility (SVG output only).
description(String) - Method in class smile.plot.vega.Concat
 
description(String) - Method in class smile.plot.vega.Facet
 
description(String) - Method in class smile.plot.vega.Legend
Sets the text description of this legend for ARIA accessibility (SVG output only).
description(String) - Method in class smile.plot.vega.Mark
Sets the description.
description(String) - Method in class smile.plot.vega.Repeat
 
description(String) - Method in class smile.plot.vega.VegaLite
Sets the description of this mark for commenting purpose.
description(String) - Method in class smile.plot.vega.View
 
det() - Method in class smile.math.matrix.BandMatrix.Cholesky
Returns the matrix determinant.
det() - Method in class smile.math.matrix.BandMatrix.LU
Returns the matrix determinant.
det() - Method in class smile.math.matrix.BigMatrix.Cholesky
Returns the matrix determinant.
det() - Method in class smile.math.matrix.BigMatrix.LU
Returns the matrix determinant.
det() - Method in class smile.math.matrix.fp32.BandMatrix.Cholesky
Returns the matrix determinant.
det() - Method in class smile.math.matrix.fp32.BandMatrix.LU
Returns the matrix determinant.
det() - Method in class smile.math.matrix.fp32.Matrix.Cholesky
Returns the matrix determinant.
det() - Method in class smile.math.matrix.fp32.Matrix.LU
Returns the matrix determinant.
det() - Method in class smile.math.matrix.fp32.SymmMatrix.BunchKaufman
Returns the matrix determinant.
det() - Method in class smile.math.matrix.fp32.SymmMatrix.Cholesky
Returns the matrix determinant.
det() - Method in class smile.math.matrix.Matrix.Cholesky
Returns the matrix determinant.
det() - Method in class smile.math.matrix.Matrix.LU
Returns the matrix determinant.
det() - Method in class smile.math.matrix.SymmMatrix.BunchKaufman
Returns the matrix determinant.
det() - Method in class smile.math.matrix.SymmMatrix.Cholesky
Returns the matrix determinant.
detach() - Method in class smile.deep.tensor.Tensor
Returns a new tensor, detached from the current graph.
detach(AutoCloseable...) - Method in class smile.util.AutoScope
Detaches resources from this Scope.
DeterministicAnnealing - Class in smile.clustering
Deterministic annealing clustering.
DeterministicAnnealing(double, double[][], int[]) - Constructor for class smile.clustering.DeterministicAnnealing
Constructor.
deviance - Variable in class smile.glm.GLM
The deviance = 2 * (LogLikelihood(Saturated Model) - LogLikelihood(Proposed Model)).
deviance() - Method in class smile.base.cart.DecisionNode
 
deviance() - Method in class smile.base.cart.InternalNode
 
deviance() - Method in interface smile.base.cart.Node
Returns the deviance of node.
deviance() - Method in class smile.base.cart.RegressionNode
 
deviance() - Method in class smile.glm.GLM
Returns the deviance of model.
deviance(double[], double[], double[]) - Method in interface smile.glm.model.Model
The deviance function.
deviance(int[], double[]) - Static method in class smile.base.cart.DecisionNode
Returns the deviance of node.
devianceResiduals - Variable in class smile.glm.GLM
The deviance residuals.
devianceResiduals() - Method in class smile.glm.GLM
Returns the deviance residuals.
device() - Static method in interface smile.deep.CUDA
Returns the default CUDA device.
device() - Method in class smile.deep.Model
Returns the device on which the model is stored.
device() - Method in class smile.deep.tensor.Tensor
Returns the device on which the tensor is.
device(byte) - Static method in interface smile.deep.CUDA
Returns the CUDA device of given index.
device(Device) - Method in class smile.deep.tensor.Tensor.Options
Sets a compute device on which a tensor is stored.
Device - Class in smile.deep.tensor
The compute device on which a tensor is stored.
Device(DeviceType) - Constructor for class smile.deep.tensor.Device
Constructor.
Device(DeviceType, byte) - Constructor for class smile.deep.tensor.Device
Constructor.
deviceCount() - Static method in interface smile.deep.CUDA
Returns the number of CUDA devices.
DeviceType - Enum Class in smile.deep.tensor
The compute device type.
df - Variable in class smile.glm.GLM
The degrees of freedom of the residual deviance.
df - Variable in class smile.stat.hypothesis.ChiSqTest
The degree of freedom of chi-square statistic.
df - Variable in class smile.stat.hypothesis.CorTest
The degree of freedom of test statistic.
df - Variable in class smile.stat.hypothesis.TTest
The degree of freedom of t-statistic.
df - Variable in class smile.timeseries.BoxTest
The degree of freedom.
df() - Method in class smile.regression.LinearModel
Returns the degree-of-freedom of residual standard error.
df() - Method in class smile.timeseries.AR
Returns the degree-of-freedom of residual standard error.
df() - Method in class smile.timeseries.ARMA
Returns the degree-of-freedom of residual standard error.
df1 - Variable in class smile.stat.hypothesis.FTest
The degree of freedom of F-statistic.
df2 - Variable in class smile.stat.hypothesis.FTest
The degree of freedom of F-statistic.
dfs() - Method in class smile.graph.AdjacencyList
 
dfs() - Method in class smile.graph.AdjacencyMatrix
 
dfs() - Method in interface smile.graph.Graph
Depth-first search connected components of graph.
dfs(Visitor) - Method in class smile.graph.AdjacencyList
 
dfs(Visitor) - Method in class smile.graph.AdjacencyMatrix
 
dfs(Visitor) - Method in interface smile.graph.Graph
DFS search on graph and performs some operation defined in visitor on each vertex during traveling.
diag() - Method in class smile.math.matrix.BigMatrix.EVD
Returns the block diagonal eigenvalue matrix whose diagonal are the real part of eigenvalues, lower subdiagonal are positive imaginary parts, and upper subdiagonal are negative imaginary parts.
diag() - Method in class smile.math.matrix.BigMatrix.SVD
Returns the diagonal matrix of singular values.
diag() - Method in class smile.math.matrix.fp32.IMatrix
Returns the diagonal elements.
diag() - Method in class smile.math.matrix.fp32.Matrix.EVD
Returns the block diagonal eigenvalue matrix whose diagonal are the real part of eigenvalues, lower subdiagonal are positive imaginary parts, and upper subdiagonal are negative imaginary parts.
diag() - Method in class smile.math.matrix.fp32.Matrix.SVD
Returns the diagonal matrix of singular values.
diag() - Method in class smile.math.matrix.fp32.SparseMatrix
 
diag() - Method in class smile.math.matrix.IMatrix
Returns the diagonal elements.
diag() - Method in class smile.math.matrix.Matrix.EVD
Returns the block diagonal eigenvalue matrix whose diagonal are the real part of eigenvalues, lower subdiagonal are positive imaginary parts, and upper subdiagonal are negative imaginary parts.
diag() - Method in class smile.math.matrix.Matrix.SVD
Returns the diagonal matrix of singular values.
diag() - Method in class smile.math.matrix.SparseMatrix
 
diag(double[]) - Static method in class smile.math.matrix.BigMatrix
Returns a square diagonal matrix.
diag(double[]) - Static method in class smile.math.matrix.Matrix
Returns a square diagonal matrix.
diag(float[]) - Static method in class smile.math.matrix.fp32.Matrix
Returns a square diagonal matrix.
diag(int, double) - Static method in class smile.math.matrix.BigMatrix
Returns a square diagonal matrix.
diag(int, double) - Static method in class smile.math.matrix.Matrix
Returns a square diagonal matrix.
diag(int, float) - Static method in class smile.math.matrix.fp32.Matrix
Returns a square diagonal matrix.
diag(int, int, double) - Static method in class smile.math.matrix.BigMatrix
Returns an m-by-n diagonal matrix.
diag(int, int, double) - Static method in class smile.math.matrix.Matrix
Returns an m-by-n diagonal matrix.
diag(int, int, float) - Static method in class smile.math.matrix.fp32.Matrix
Returns an m-by-n diagonal matrix.
diag(DoublePointer) - Static method in class smile.math.matrix.BigMatrix
Returns a square diagonal matrix.
Diag - Enum Class in smile.math.blas
The flag if a triangular matrix has unit diagonal elements.
diagonal - Variable in class smile.stat.distribution.MultivariateGaussianDistribution
True if the covariance matrix is diagonal.
dialogResultValue - Variable in class smile.swing.FontChooser
 
Dictionary - Interface in smile.nlp.dictionary
A dictionary is a set of words in some natural language.
diff(double[], int) - Static method in interface smile.timeseries.TimeSeries
Returns the first-differencing of time series.
diff(double[], int, int) - Static method in interface smile.timeseries.TimeSeries
Returns the differencing of time series.
DifferentiableFunction - Interface in smile.math
A differentiable function is a function whose derivative exists at each point in its domain.
DifferentiableMultivariateFunction - Interface in smile.math
A differentiable function is a function whose derivative exists at each point in its domain.
digamma(double) - Static method in class smile.math.special.Gamma
The digamma function is defined as the logarithmic derivative of the gamma function.
DIGITS - Static variable in class smile.math.MathEx
The number of digits (in radix base) in the mantissa.
dijkstra() - Method in interface smile.graph.Graph
Calculates the all pair shortest path by Dijkstra algorithm.
dijkstra(int) - Method in class smile.graph.AdjacencyList
 
dijkstra(int) - Method in class smile.graph.AdjacencyMatrix
 
dijkstra(int) - Method in interface smile.graph.Graph
Calculate the shortest path from a source to all other vertices in the graph by Dijkstra algorithm.
dijkstra(int, boolean) - Method in class smile.graph.AdjacencyMatrix
Calculates the shortest path by Dijkstra algorithm.
dilation() - Method in record class smile.vision.layer.Conv2dNormActivation.Options
Returns the value of the dilation record component.
dim() - Method in class smile.deep.tensor.Tensor
Returns the number of dimensions of tensor.
dimension() - Method in class smile.classification.Maxent
Returns the dimension of input space.
dimension() - Method in class smile.nlp.embedding.Word2Vec
Returns the dimension of embedding vector space.
dimFeedForward() - Method in record class smile.llm.Transformer.Options
Returns the value of the dimFeedForward record component.
dir() - Static method in interface smile.util.CacheFiles
Returns the cache directory path.
direction(String) - Method in class smile.plot.vega.Legend
Sets the direction of the legend, one of "vertical" or "horizontal".
DiscreteDistribution - Class in smile.stat.distribution
Univariate discrete distributions.
DiscreteDistribution() - Constructor for class smile.stat.distribution.DiscreteDistribution
 
DiscreteExponentialFamily - Interface in smile.stat.distribution
The purpose of this interface is mainly to define the method M that is the Maximization step in the EM algorithm.
DiscreteExponentialFamilyMixture - Class in smile.stat.distribution
The finite mixture of distributions from discrete exponential family.
DiscreteExponentialFamilyMixture(DiscreteMixture.Component...) - Constructor for class smile.stat.distribution.DiscreteExponentialFamilyMixture
Constructor.
discreteHeight(int) - Method in class smile.plot.vega.ViewConfig
Sets the default height when the plot has non arc marks and either a discrete y-field or no y-field.
DiscreteMixture - Class in smile.stat.distribution
The finite mixture of discrete distributions.
DiscreteMixture(DiscreteMixture.Component...) - Constructor for class smile.stat.distribution.DiscreteMixture
Constructor.
DiscreteMixture.Component - Class in smile.stat.distribution
A component in the mixture distribution is defined by a distribution and its weight in the mixture.
DiscreteNaiveBayes - Class in smile.classification
Naive Bayes classifier for document classification in NLP.
DiscreteNaiveBayes(DiscreteNaiveBayes.Model, double[], int) - Constructor for class smile.classification.DiscreteNaiveBayes
Constructor of naive Bayes classifier for document classification.
DiscreteNaiveBayes(DiscreteNaiveBayes.Model, double[], int, double, IntSet) - Constructor for class smile.classification.DiscreteNaiveBayes
Constructor of naive Bayes classifier for document classification.
DiscreteNaiveBayes(DiscreteNaiveBayes.Model, int, int) - Constructor for class smile.classification.DiscreteNaiveBayes
Constructor of naive Bayes classifier for document classification.
DiscreteNaiveBayes(DiscreteNaiveBayes.Model, int, int, double, IntSet) - Constructor for class smile.classification.DiscreteNaiveBayes
Constructor of naive Bayes classifier for document classification.
DiscreteNaiveBayes.Model - Enum Class in smile.classification
The generation models of naive Bayes classifier.
discreteWidth(int) - Method in class smile.plot.vega.ViewConfig
Sets the default width when the plot has non-arc marks and either a discrete x-field or no x-field.
distance - Variable in class smile.neighbor.Neighbor
The distance between the query and the neighbor.
distance - Variable in class smile.vq.hebb.Neuron
The distance between the neuron and an input signal.
distance(double[]) - Method in class smile.vq.hebb.Neuron
Computes the distance between the neuron and a signal.
distance(double[], double[]) - Method in class smile.clustering.DeterministicAnnealing
 
distance(double[], double[]) - Method in class smile.clustering.GMeans
 
distance(double[], double[]) - Method in class smile.clustering.KMeans
 
distance(double[], double[]) - Method in class smile.clustering.XMeans
 
distance(double[], double[]) - Static method in class smile.math.MathEx
The Euclidean distance.
distance(double[], SparseArray) - Method in class smile.clustering.SIB
 
distance(float[], float[]) - Static method in class smile.math.MathEx
The Euclidean distance.
distance(int[], int[]) - Method in class smile.clustering.KModes
 
distance(int[], int[]) - Static method in class smile.math.MathEx
The Euclidean distance on binary sparse arrays, which are the indices of nonzero elements in ascending order.
distance(SparseArray, SparseArray) - Static method in class smile.math.MathEx
The Euclidean distance.
distance(T, T) - Method in class smile.clustering.CLARANS
 
distance(T, U) - Method in class smile.clustering.CentroidClustering
The distance function.
Distance<T> - Interface in smile.math.distance
An interface to calculate a distance measure between two objects.
distinct() - Method in interface smile.data.vector.Vector
Returns the distinct values.
distortion - Variable in class smile.clustering.CentroidClustering
The total distortion.
distortion - Variable in class smile.clustering.SpectralClustering
The distortion in feature space.
distribution - Variable in class smile.stat.distribution.DiscreteMixture.Component
The distribution of component.
distribution - Variable in class smile.stat.distribution.Mixture.Component
The distribution of component.
distribution - Variable in class smile.stat.distribution.MultivariateMixture.Component
The distribution of component.
Distribution - Interface in smile.stat.distribution
Probability distribution of univariate random variable.
div(double) - Method in class smile.deep.tensor.Tensor
Returns A / b.
div(double) - Method in class smile.math.matrix.BigMatrix
A /= b
div(double) - Method in class smile.math.matrix.Matrix
A /= b
div(double) - Method in class smile.util.Array2D
A /= x.
div(float) - Method in class smile.deep.tensor.Tensor
Returns A / b.
div(float) - Method in class smile.math.matrix.fp32.Matrix
A /= b
div(int) - Method in class smile.util.IntArray2D
A /= x.
div(int, int, double) - Method in class smile.math.matrix.BigMatrix
A[i,j] /= b
div(int, int, double) - Method in class smile.math.matrix.Matrix
A[i,j] /= b
div(int, int, double) - Method in class smile.util.Array2D
A[i, j] /= x.
div(int, int, float) - Method in class smile.math.matrix.fp32.Matrix
A[i,j] /= b
div(int, int, int) - Method in class smile.util.IntArray2D
A[i, j] /= x.
div(String, String) - Static method in interface smile.data.formula.Terms
Divides two terms.
div(String, Term) - Static method in interface smile.data.formula.Terms
Divides two terms.
div(Term, String) - Static method in interface smile.data.formula.Terms
Divides two terms.
div(Term, Term) - Static method in interface smile.data.formula.Terms
Divides two terms.
div(Tensor) - Method in class smile.deep.tensor.Tensor
Returns A / B element wisely.
div(Complex) - Method in class smile.math.Complex
Returns a / b.
div(BigMatrix) - Method in class smile.math.matrix.BigMatrix
Element-wise division A /= B
div(Matrix) - Method in class smile.math.matrix.fp32.Matrix
Element-wise division A /= B
div(Matrix) - Method in class smile.math.matrix.Matrix
Element-wise division A /= B
div(Array2D) - Method in class smile.util.Array2D
A /= B.
div(IntArray2D) - Method in class smile.util.IntArray2D
A /= B.
Div - Class in smile.data.formula
The term of a / b expression.
Div(Term, Term) - Constructor for class smile.data.formula.Div
Constructor.
div_(double) - Method in class smile.deep.tensor.Tensor
Returns A /= b.
div_(float) - Method in class smile.deep.tensor.Tensor
Returns A /= b.
div_(Tensor) - Method in class smile.deep.tensor.Tensor
Returns A /= B element wisely.
divide(int...) - Method in class smile.plot.vega.BinParams
Sets the scale factors indicating allowable subdivisions.
dlink(double) - Method in interface smile.glm.model.Model
The derivative of link function.
dModel() - Method in record class smile.llm.Transformer.Options
Returns the value of the dModel record component.
domain(boolean) - Method in class smile.plot.vega.Axis
Sets if the domain (the axis baseline) should be included as part of the axis.
domain(double...) - Method in class smile.plot.vega.Field
Sets the customize domain values.
domain(String...) - Method in class smile.plot.vega.Field
Sets the customize domain values.
domainCap(String) - Method in class smile.plot.vega.Axis
Sets the stroke cap for the domain line's ending style.
domainColor(String) - Method in class smile.plot.vega.Axis
Sets the color of axis domain line.
domainDash(double, double) - Method in class smile.plot.vega.Axis
Sets the alternating [stroke, space] lengths for dashed domain lines.
domainDashOffset(double) - Method in class smile.plot.vega.Axis
Sets the pixel offset at which to start drawing with the domain dash array.
domainMax(double) - Method in class smile.plot.vega.Field
Sets the maximum value in the scale domain, overriding the domain property or the default domain.
domainMax(String) - Method in class smile.plot.vega.Field
Sets the maximum value in the scale domain, overriding the domain property or the default domain.
domainMin(double) - Method in class smile.plot.vega.Field
Sets the minimum value in the scale domain, overriding the domain property or the default domain.
domainMin(String) - Method in class smile.plot.vega.Field
Sets the minimum value in the scale domain, overriding the domain property or the default domain.
domainOpacity(double) - Method in class smile.plot.vega.Axis
Sets the opacity of the axis domain line.
domainWidth(double) - Method in class smile.plot.vega.Axis
Sets the stroke width of axis domain line.
dot() - Method in class smile.base.cart.CART
Returns the graphic representation in Graphviz dot format.
dot() - Static method in interface smile.data.formula.Terms
Returns the special term "." that means all columns not otherwise in the formula in the context of a data frame.
dot(double[], double[]) - Method in interface smile.math.blas.BLAS
Computes the dot product of two vectors.
dot(double[], double[]) - Static method in class smile.math.MathEx
Returns the dot product between two vectors.
dot(float[], float[]) - Method in interface smile.math.blas.BLAS
Computes the dot product of two vectors.
dot(float[], float[]) - Static method in class smile.math.MathEx
Returns the dot product between two vectors.
dot(int[], int[]) - Static method in class smile.math.MathEx
Returns the dot product between two binary sparse arrays, which are the indices of nonzero elements in ascending order.
dot(int, double[], int, double[], int) - Method in interface smile.math.blas.BLAS
Computes the dot product of two vectors.
dot(int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
dot(int, float[], int, float[], int) - Method in interface smile.math.blas.BLAS
Computes the dot product of two vectors.
dot(int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
dot(StructType, StructField, int) - Method in class smile.base.cart.DecisionNode
 
dot(StructType, StructField, int) - Method in interface smile.base.cart.Node
Returns the dot representation of node.
dot(StructType, StructField, int) - Method in class smile.base.cart.NominalNode
 
dot(StructType, StructField, int) - Method in class smile.base.cart.OrdinalNode
 
dot(StructType, StructField, int) - Method in class smile.base.cart.RegressionNode
 
dot(SparseArray, SparseArray) - Static method in class smile.math.MathEx
Returns the dot product between two sparse arrays.
DOT - Enum constant in enum class smile.plot.swing.Line.Style
 
DOT_DASH - Enum constant in enum class smile.plot.swing.Line.Style
 
DotProductKernel - Interface in smile.math.kernel
Dot product kernel depends only on the dot product of x and y.
Double - Enum constant in enum class smile.data.type.DataType.ID
Double type ID.
DOUBLE - Static variable in interface smile.util.Regex
Double regular expression pattern.
DOUBLE_REGEX - Static variable in interface smile.util.Regex
Double regular expression.
DoubleArrayCellEditor - Class in smile.swing.table
Implements a cell editor that uses a formatted text field to edit double[] values.
DoubleArrayCellEditor() - Constructor for class smile.swing.table.DoubleArrayCellEditor
Constructor.
DoubleArrayCellRenderer - Class in smile.swing.table
Double array renderer in JTable.
DoubleArrayCellRenderer() - Constructor for class smile.swing.table.DoubleArrayCellRenderer
Constructor.
DoubleArrayList - Class in smile.util
A resizeable, array-backed list of double primitives.
DoubleArrayList() - Constructor for class smile.util.DoubleArrayList
Constructs an empty list.
DoubleArrayList(double[]) - Constructor for class smile.util.DoubleArrayList
Constructs a list containing the values of the specified array.
DoubleArrayList(int) - Constructor for class smile.util.DoubleArrayList
Constructs an empty list with the specified initial capacity.
DoubleArrayType - Static variable in class smile.data.type.DataTypes
Double Array data type.
DoubleCellEditor - Class in smile.swing.table
Implements a cell editor that uses a formatted text field to edit Double values.
DoubleCellEditor() - Constructor for class smile.swing.table.DoubleCellEditor
Constructor.
DoubleCellEditor(double, double) - Constructor for class smile.swing.table.DoubleCellEditor
Constructor.
DoubleConsumer - Interface in smile.math.matrix
Double precision matrix element stream consumer.
DoubleFunction - Class in smile.data.formula
The generic term of applying a double function.
DoubleFunction(String, Term, Function) - Constructor for class smile.data.formula.DoubleFunction
Constructor.
DoubleHeapSelect - Class in smile.sort
This class tracks the smallest values seen thus far in a stream of values.
DoubleHeapSelect(double[]) - Constructor for class smile.sort.DoubleHeapSelect
Constructor.
DoubleHeapSelect(int) - Constructor for class smile.sort.DoubleHeapSelect
Constructor.
DoubleObjectType - Static variable in class smile.data.type.DataTypes
Double Object data type.
DoubleType - Class in smile.data.type
Double data type.
DoubleType - Static variable in class smile.data.type.DataTypes
Double data type.
doubleValue() - Method in class smile.deep.tensor.Tensor
Returns the double value when the tensor holds a single value.
doubleVector(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
doubleVector(int) - Method in class smile.data.IndexDataFrame
 
doubleVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
doubleVector(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
DoubleVector - Interface in smile.data.vector
An immutable double vector.
download(String) - Static method in interface smile.util.CacheFiles
Downloads a file and save to the cache directory.
download(String, boolean) - Static method in interface smile.util.CacheFiles
Downloads a file and save to the cache directory.
drawLine(double[]...) - Method in class smile.plot.swing.Graphics
Draw poly line.
drawLineBaseRatio(double[]...) - Method in class smile.plot.swing.Graphics
Draw poly line.
drawPoint(char, double...) - Method in class smile.plot.swing.Graphics
Draw a dot with given pattern.
drawPoint(double...) - Method in class smile.plot.swing.Graphics
Draw a dot.
drawPolygon(double[]...) - Method in class smile.plot.swing.Graphics
Draw polygon.
drawRect(double[], double[]) - Method in class smile.plot.swing.Graphics
Draw the outline of the specified rectangle.
drawRectBaseRatio(double[], double[]) - Method in class smile.plot.swing.Graphics
Draw the outline of the specified rectangle.
drawText(String, double[]) - Method in class smile.plot.swing.Graphics
Draw a string.
drawText(String, double[], double) - Method in class smile.plot.swing.Graphics
Draw a string with given rotation angle.
drawText(String, double[], double, double) - Method in class smile.plot.swing.Graphics
Draw a string with given reference point.
drawText(String, double[], double, double, double) - Method in class smile.plot.swing.Graphics
Draw a string with given reference point and rotation angle.
drawTextBaseRatio(String, double[]) - Method in class smile.plot.swing.Graphics
Draw a string with given rotation angle.
drawTextBaseRatio(String, double[], double) - Method in class smile.plot.swing.Graphics
Draw a string with given rotation angle.
drawTextBaseRatio(String, double[], double, double) - Method in class smile.plot.swing.Graphics
Draw a string with given reference point.
drawTextBaseRatio(String, double[], double, double, double) - Method in class smile.plot.swing.Graphics
Draw a string with given reference point and rotation angle.
drop(int...) - Method in interface smile.data.DataFrame
Returns a new DataFrame without selected columns.
drop(int...) - Method in class smile.data.IndexDataFrame
 
drop(String...) - Method in interface smile.data.DataFrame
Returns a new DataFrame without selected columns.
dropout - Variable in class smile.base.mlp.Layer
The dropout rate.
dropout - Variable in class smile.base.mlp.LayerBuilder
The dropout rate.
dropout() - Method in record class smile.llm.Transformer.Options
Returns the value of the dropout record component.
dropout(double) - Static method in interface smile.deep.layer.Layer
Returns a dropout layer that randomly zeroes some of the elements of the input tensor with probability p during training.
dropout(double) - Method in class smile.deep.tensor.Tensor
Randomly zeroes some elements of the input tensor with probability p.
dropout_(double) - Method in class smile.deep.tensor.Tensor
Randomly zeroes some elements in place with probability p.
DropoutLayer - Class in smile.deep.layer
A dropout layer that randomly zeroes some of the elements of the input tensor with probability p during training.
DropoutLayer(double) - Constructor for class smile.deep.layer.DropoutLayer
Constructor.
DropoutLayer(double, boolean) - Constructor for class smile.deep.layer.DropoutLayer
Constructor.
dsv(String, String) - Method in class smile.plot.vega.Data
Loads a delimited text file with a custom delimiter.
dsv(String, String, Map<String, String>) - Method in class smile.plot.vega.Data
Loads a delimited text file with a custom delimiter.
DT - Enum constant in enum class smile.nlp.pos.PennTreebankPOS
Determiner.
dtype() - Method in class smile.deep.tensor.Tensor
Returns the element data type.
dtype(ScalarType) - Method in class smile.deep.tensor.Tensor.Options
Sets the data type of the elements stored in the tensor.
DUMMY - Enum constant in enum class smile.data.CategoricalEncoder
Dummy encoding.
DynamicTimeWarping<T> - Class in smile.math.distance
Dynamic time warping is an algorithm for measuring similarity between two sequences which may vary in time or speed.
DynamicTimeWarping(Distance<T>) - Constructor for class smile.math.distance.DynamicTimeWarping
Constructor.
DynamicTimeWarping(Distance<T>, double) - Constructor for class smile.math.distance.DynamicTimeWarping
Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.

E

Edge - Class in smile.vq.hebb
The connection between neurons.
Edge(int, int, double) - Constructor for class smile.graph.Graph.Edge
Constructor.
Edge(Neuron) - Constructor for class smile.vq.hebb.Edge
Constructor.
Edge(Neuron, int) - Constructor for class smile.vq.hebb.Edge
Constructor.
edges - Variable in class smile.vq.hebb.Neuron
The direct connected neighbors.
EditDistance - Class in smile.math.distance
The Edit distance between two strings is a metric for measuring the amount of difference between two sequences.
EditDistance() - Constructor for class smile.math.distance.EditDistance
Constructor.
EditDistance(boolean) - Constructor for class smile.math.distance.EditDistance
Constructor.
EditDistance(int) - Constructor for class smile.math.distance.EditDistance
Constructor.
EditDistance(int[][]) - Constructor for class smile.math.distance.EditDistance
Constructor.
EditDistance(int[][], double) - Constructor for class smile.math.distance.EditDistance
Constructor.
EditDistance(int, boolean) - Constructor for class smile.math.distance.EditDistance
Constructor.
EfficientNet - Class in smile.vision
EfficientNet is an image classification model family.
EfficientNet(MBConvConfig[], double, double, int, int, IntFunction<Layer>) - Constructor for class smile.vision.EfficientNet
Constructor.
eigen() - Method in class smile.math.matrix.BigMatrix
Eigenvalue Decomposition.
eigen() - Method in class smile.math.matrix.fp32.Matrix
Eigenvalue Decomposition.
eigen() - Method in class smile.math.matrix.Matrix
Eigenvalue Decomposition.
eigen(boolean, boolean, boolean) - Method in class smile.math.matrix.BigMatrix
Eigenvalue Decomposition.
eigen(boolean, boolean, boolean) - Method in class smile.math.matrix.fp32.Matrix
Eigenvalue Decomposition.
eigen(boolean, boolean, boolean) - Method in class smile.math.matrix.Matrix
Eigenvalue Decomposition.
eigen(double[]) - Method in class smile.math.matrix.IMatrix
Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.
eigen(double[], double, double, int) - Method in class smile.math.matrix.IMatrix
Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.
eigen(float[]) - Method in class smile.math.matrix.fp32.IMatrix
Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.
eigen(float[], float, float, int) - Method in class smile.math.matrix.fp32.IMatrix
Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.
eigen(IMatrix, ARPACK.AsymmOption, int) - Static method in class smile.math.matrix.fp32.ARPACK
Computes NEV eigenvalues of an asymmetric single precision matrix.
eigen(IMatrix, ARPACK.AsymmOption, int, int, float) - Static method in class smile.math.matrix.fp32.ARPACK
Computes NEV eigenvalues of an asymmetric single precision matrix.
eigen(IMatrix, int) - Static method in class smile.math.matrix.Lanczos
Find k-largest approximate eigen pairs of a symmetric matrix by the Lanczos algorithm.
eigen(IMatrix, int, double, int) - Static method in class smile.math.matrix.Lanczos
Find k-largest approximate eigen pairs of a symmetric matrix by the Lanczos algorithm.
eigen(IMatrix, ARPACK.AsymmOption, int) - Static method in class smile.math.matrix.ARPACK
Computes NEV eigenvalues of an asymmetric double precision matrix.
eigen(IMatrix, ARPACK.AsymmOption, int, int, double) - Static method in class smile.math.matrix.ARPACK
Computes NEV eigenvalues of an asymmetric double precision matrix.
EigenRange - Enum Class in smile.math.blas
THe option of eigenvalue range.
ElasticNet - Class in smile.regression
Elastic Net regularization.
ElasticNet() - Constructor for class smile.regression.ElasticNet
 
Ellipsis - Static variable in class smile.deep.tensor.Index
The ellipsis (...) is used to slice higher-dimensional data structures as in numpy.
EMAIL_ADDRESS - Static variable in interface smile.util.Regex
Email address.
embedding(int, int) - Static method in interface smile.deep.layer.Layer
Returns an embedding layer that is a simple lookup table that stores embeddings of a fixed dictionary and size.
embedding(int, int, double) - Static method in interface smile.deep.layer.Layer
Returns an embedding layer that is a simple lookup table that stores embeddings of a fixed dictionary and size.
EmbeddingLayer - Class in smile.deep.layer
An embedding layer that is a simple lookup table that stores embeddings of a fixed dictionary and size.
EmbeddingLayer(int, int) - Constructor for class smile.deep.layer.EmbeddingLayer
Constructor.
EmbeddingLayer(int, int, double) - Constructor for class smile.deep.layer.EmbeddingLayer
Constructor.
EmpiricalDistribution - Class in smile.stat.distribution
An empirical distribution function or empirical cdf, is a cumulative probability distribution function that concentrates probability 1/n at each of the n numbers in a sample.
EmpiricalDistribution(double[]) - Constructor for class smile.stat.distribution.EmpiricalDistribution
Constructor.
EmpiricalDistribution(double[], IntSet) - Constructor for class smile.stat.distribution.EmpiricalDistribution
Constructor.
empty(long...) - Static method in class smile.deep.tensor.Tensor
Returns a tensor with uninitialized data.
empty(Tensor.Options, long...) - Static method in class smile.deep.tensor.Tensor
Returns a tensor with uninitialized data.
emptyCache() - Method in class smile.deep.tensor.Device
Releases all unoccupied cached memory.
encode(String) - Method in class smile.llm.tokenizer.SentencePiece
 
encode(String) - Method in class smile.llm.tokenizer.Tiktoken
 
encode(String) - Method in interface smile.llm.tokenizer.Tokenizer
Encodes a string into a list of token IDs.
encode(String, boolean, boolean) - Method in class smile.llm.tokenizer.SentencePiece
 
encode(String, boolean, boolean) - Method in class smile.llm.tokenizer.Tiktoken
 
encode(String, boolean, boolean) - Method in interface smile.llm.tokenizer.Tokenizer
Encodes a string into a list of token IDs.
encode(String, String) - Method in class smile.plot.vega.View
Returns the field object for encoding a channel.
encodeDatum(String, double) - Method in class smile.plot.vega.Layer
 
encodeDatum(String, double) - Method in class smile.plot.vega.View
Sets a constant data value encoded via a scale.
encodeDatum(String, int) - Method in class smile.plot.vega.Layer
 
encodeDatum(String, int) - Method in class smile.plot.vega.View
Sets a constant data value encoded via a scale.
encodeDatum(String, String) - Method in class smile.plot.vega.Layer
 
encodeDatum(String, String) - Method in class smile.plot.vega.View
Sets a constant data value encoded via a scale.
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 class smile.association.AssociationRule
 
equals(Object) - Method in class smile.association.ItemSet
 
equals(Object) - Method in class smile.base.cart.DecisionNode
 
equals(Object) - Method in class smile.base.cart.RegressionNode
 
equals(Object) - Method in class smile.data.formula.Formula
 
equals(Object) - Method in class smile.data.measure.CategoricalMeasure
 
equals(Object) - Method in class smile.data.measure.NominalScale
 
equals(Object) - Method in class smile.data.measure.OrdinalScale
 
equals(Object) - Method in record class smile.data.SampleInstance
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class smile.data.type.ArrayType
 
equals(Object) - Method in class smile.data.type.BooleanType
 
equals(Object) - Method in class smile.data.type.ByteType
 
equals(Object) - Method in class smile.data.type.CharType
 
equals(Object) - Method in class smile.data.type.DateTimeType
 
equals(Object) - Method in class smile.data.type.DateType
 
equals(Object) - Method in class smile.data.type.DecimalType
 
equals(Object) - Method in class smile.data.type.DoubleType
 
equals(Object) - Method in class smile.data.type.FloatType
 
equals(Object) - Method in class smile.data.type.IntegerType
 
equals(Object) - Method in class smile.data.type.LongType
 
equals(Object) - Method in class smile.data.type.ObjectType
 
equals(Object) - Method in class smile.data.type.ShortType
 
equals(Object) - Method in class smile.data.type.StringType
 
equals(Object) - Method in class smile.data.type.StructField
 
equals(Object) - Method in class smile.data.type.StructType
 
equals(Object) - Method in class smile.data.type.TimeType
 
equals(Object) - Method in record class smile.deep.SampleBatch
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class smile.deep.tensor.Device
 
equals(Object) - Method in class smile.deep.tensor.Tensor
 
equals(Object) - Method in record class smile.llm.llama.Message
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class smile.llm.Transformer.Options
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class smile.math.Complex
 
equals(Object) - Method in class smile.math.matrix.BandMatrix
 
equals(Object) - Method in class smile.math.matrix.BigMatrix
 
equals(Object) - Method in class smile.math.matrix.fp32.BandMatrix
 
equals(Object) - Method in class smile.math.matrix.fp32.Matrix
 
equals(Object) - Method in class smile.math.matrix.fp32.SymmMatrix
 
equals(Object) - Method in class smile.math.matrix.Matrix
 
equals(Object) - Method in class smile.math.matrix.SymmMatrix
 
equals(Object) - Method in class smile.nlp.Bigram
 
equals(Object) - Method in class smile.nlp.NGram
 
equals(Object) - Method in class smile.nlp.SimpleText
 
equals(Object) - Method in record class smile.plot.vega.SortField
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class smile.plot.vega.WindowTransformField
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class smile.util.Bytes
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class smile.util.IntPair
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class smile.util.Tuple2
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class smile.vision.layer.Conv2dNormActivation.Options
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class smile.vision.layer.MBConvConfig
Indicates whether some other object is "equal to" this one.
equals(BandMatrix, double) - Method in class smile.math.matrix.BandMatrix
Returns true if two matrices equal in given precision.
equals(BigMatrix, double) - Method in class smile.math.matrix.BigMatrix
Returns true if two matrices equal in given precision.
equals(BandMatrix, float) - Method in class smile.math.matrix.fp32.BandMatrix
Returns true if two matrices equal in given precision.
equals(Matrix, float) - Method in class smile.math.matrix.fp32.Matrix
Returns true if two matrices equal in given precision.
equals(SymmMatrix, float) - Method in class smile.math.matrix.fp32.SymmMatrix
Returns true if two matrices equal in given precision.
equals(Matrix, double) - Method in class smile.math.matrix.Matrix
Returns true if two matrices equal in given precision.
equals(SymmMatrix, double) - Method in class smile.math.matrix.SymmMatrix
Returns true if two matrices equal in given precision.
erf(double) - Static method in class smile.math.special.Erf
The Gauss error function.
Erf - Class in smile.math.special
The error function.
erfc(double) - Static method in class smile.math.special.Erf
The complementary error function.
erfcc(double) - Static method in class smile.math.special.Erf
The complementary error function with fractional error everywhere less than 1.2 × 10-7.
error - Variable in class smile.validation.ClassificationMetrics
The number of errors.
error() - Method in class smile.regression.LinearModel
Returns the residual standard error.
Error - Class in smile.validation.metric
The number of errors in the population.
Error() - Constructor for class smile.validation.metric.Error
 
ERROR_OPTION - Static variable in class smile.swing.FontChooser
Return value from showDialog().
estimate(int, double) - Method in class smile.neighbor.lsh.HashValueParzenModel
Given a hash value h, estimate the Gaussian model (mean and variance) of neighbors existing in the corresponding bucket.
EuclideanDistance - Class in smile.math.distance
Euclidean distance.
EuclideanDistance() - Constructor for class smile.math.distance.EuclideanDistance
Constructor.
EuclideanDistance(double[]) - Constructor for class smile.math.distance.EuclideanDistance
Constructor with a given weight vector.
eval() - Method in class smile.deep.Model
Sets the model in the evaluation/inference mode.
eval(Dataset, Metric...) - Method in class smile.deep.Model
Evaluates the model accuracy on a test dataset.
EVD(double[], double[], Matrix, Matrix) - Constructor for class smile.math.matrix.Matrix.EVD
Constructor.
EVD(double[], Matrix) - Constructor for class smile.math.matrix.Matrix.EVD
Constructor.
EVD(float[], float[], Matrix, Matrix) - Constructor for class smile.math.matrix.fp32.Matrix.EVD
Constructor.
EVD(float[], Matrix) - Constructor for class smile.math.matrix.fp32.Matrix.EVD
Constructor.
EVD(DoublePointer, DoublePointer, BigMatrix, BigMatrix) - Constructor for class smile.math.matrix.BigMatrix.EVD
Constructor.
EVD(DoublePointer, BigMatrix) - Constructor for class smile.math.matrix.BigMatrix.EVD
Constructor.
EVDJob - Enum Class in smile.math.blas
The option if computing eigen vectors.
evolve() - Method in interface smile.gap.LamarckianChromosome
Performs a step of (hill-climbing) local search to evolve this chromosome.
evolve(int) - Method in class smile.gap.GeneticAlgorithm
Performs genetic algorithm for a given number of generations.
evolve(int, double) - Method in class smile.gap.GeneticAlgorithm
Performs genetic algorithm until the given number of generations is reached or the best fitness is larger than the given threshold.
EX - Enum constant in enum class smile.nlp.pos.PennTreebankPOS
Existential there.
execute(String) - Method in class smile.data.SQL
Executes an SQL statement, which may return multiple results.
exp() - Method in class smile.deep.tensor.Tensor
Returns the exponential of elements in the tensor.
exp() - Method in class smile.math.Complex
Returns the complex exponential.
exp(double, double) - Static method in interface smile.math.TimeFunction
Returns the exponential decay function.
exp(double, double, double) - Static method in interface smile.math.TimeFunction
Returns the exponential decay function.
exp(double, double, double, boolean) - Static method in interface smile.math.TimeFunction
Returns the exponential decay function.
exp(String) - Static method in interface smile.data.formula.Terms
The exp(x) term.
exp(Term) - Static method in interface smile.data.formula.Terms
The exp(x) term.
Exp - Class in smile.ica
The contrast function when the independent components are highly super-Gaussian, or when robustness is very important.
Exp() - Constructor for class smile.ica.Exp
 
exp_() - Method in class smile.deep.tensor.Tensor
Returns the exponential of elements in the tensor in place.
expand() - Method in class smile.data.formula.FactorCrossing
 
expand() - Method in interface smile.data.formula.Term
Expands the term (e.g.
expand() - Method in class smile.neighbor.lsh.Probe
This operation sets to one the component following the last nonzero component if it is not the last one.
expand(StructType) - Method in class smile.data.formula.Formula
Expands the Dot and FactorCrossing terms on the given schema.
expandRatio() - Method in record class smile.vision.layer.MBConvConfig
Returns the value of the expandRatio record component.
expm1(String) - Static method in interface smile.data.formula.Terms
The exp(x) - 1 term.
expm1(Term) - Static method in interface smile.data.formula.Terms
The exp(x) - 1 term.
ExponentialDistribution - Class in smile.stat.distribution
An exponential distribution describes the times between events in a Poisson process, in which events occur continuously and independently at a constant average rate.
ExponentialDistribution(double) - Constructor for class smile.stat.distribution.ExponentialDistribution
Constructor.
ExponentialFamily - Interface in smile.stat.distribution
The exponential family is a class of probability distributions sharing a certain form.
ExponentialFamilyMixture - Class in smile.stat.distribution
The finite mixture of distributions from exponential family.
ExponentialFamilyMixture(Mixture.Component...) - Constructor for class smile.stat.distribution.ExponentialFamilyMixture
Constructor.
ExponentialVariogram - Class in smile.interpolation.variogram
Exponential variogram.
ExponentialVariogram(double, double) - Constructor for class smile.interpolation.variogram.ExponentialVariogram
Constructor.
ExponentialVariogram(double, double, double) - Constructor for class smile.interpolation.variogram.ExponentialVariogram
Constructor.
extend() - Method in class smile.neighbor.lsh.Probe
This operation adds one to the last nonzero component.
extendBound(double[], double[]) - Method in class smile.plot.swing.Base
Extend lower and upper bounds.
extendBound(double[], double[]) - Method in class smile.plot.swing.Canvas
Extend lower and upper bounds.
extendBound(int) - Method in class smile.plot.swing.Base
Rounds the bounds for axis i.
extendLowerBound(double[]) - Method in class smile.plot.swing.Base
Extend lower bounds.
extendLowerBound(double[]) - Method in class smile.plot.swing.Canvas
Extend lower bounds.
extendUpperBound(double[]) - Method in class smile.plot.swing.Base
Extend upper bounds.
extendUpperBound(double[]) - Method in class smile.plot.swing.Canvas
Extend upper bounds.
extent(double, double) - Method in class smile.plot.vega.BinParams
Sets the range of desired bin values
extent(double, double) - Method in class smile.plot.vega.DensityTransform
Sets a [min, max] domain from which to sample the distribution.
extent(double, double) - Method in class smile.plot.vega.RegressionTransform
Sets a [min, max] domain over the independent (x) field for the starting and ending points of the generated trend line.
extent(String) - Method in class smile.plot.vega.Mark
Sets the extent of the band.
extent(String, String) - Method in class smile.plot.vega.Transform
Adds an extent transform.
eye(int) - Static method in class smile.math.matrix.BigMatrix
Returns an identity matrix.
eye(int) - Static method in class smile.math.matrix.fp32.Matrix
Returns an identity matrix.
eye(int) - Static method in class smile.math.matrix.Matrix
Returns an identity matrix.
eye(int, int) - Static method in class smile.math.matrix.BigMatrix
Returns an m-by-n identity matrix.
eye(int, int) - Static method in class smile.math.matrix.fp32.Matrix
Returns an m-by-n identity matrix.
eye(int, int) - Static method in class smile.math.matrix.Matrix
Returns an m-by-n identity matrix.
eye(long) - Static method in class smile.deep.tensor.Tensor
Returns an identity matrix.
eye(Tensor.Options, long) - Static method in class smile.deep.tensor.Tensor
Returns an identity matrix.

F

f - Variable in class smile.stat.hypothesis.FTest
F-statistic.
f(double) - Method in class smile.ica.Exp
 
f(double) - Method in class smile.ica.Kurtosis
 
f(double) - Method in class smile.ica.LogCosh
 
f(double) - Method in class smile.interpolation.variogram.ExponentialVariogram
 
f(double) - Method in class smile.interpolation.variogram.GaussianVariogram
 
f(double) - Method in class smile.interpolation.variogram.PowerVariogram
 
f(double) - Method in class smile.interpolation.variogram.SphericalVariogram
 
f(double) - Method in interface smile.math.Function
Computes the value of the function at x.
f(double) - Method in interface smile.math.kernel.DotProductKernel
 
f(double) - Method in interface smile.math.kernel.IsotropicKernel
 
f(double) - Method in class smile.math.kernel.Matern
 
f(double) - Method in class smile.math.rbf.GaussianRadialBasis
 
f(double) - Method in class smile.math.rbf.InverseMultiquadricRadialBasis
 
f(double) - Method in class smile.math.rbf.MultiquadricRadialBasis
 
f(double) - Method in class smile.math.rbf.ThinPlateRadialBasis
 
f(double) - Method in class smile.math.Scaler
 
f(double[]) - Method in interface smile.base.mlp.ActivationFunction
The output function.
f(double[]) - Method in enum class smile.base.mlp.OutputFunction
The output function.
f(double[]) - Method in class smile.base.svm.LinearKernelMachine
Returns the value of decision function.
f(double[]) - Method in interface smile.math.MultivariateFunction
Computes the value of the function at x.
f(int) - Method in interface smile.math.IntFunction
Computes the value of the function at x.
f(int[]) - Method in class smile.base.svm.LinearKernelMachine
Returns the value of decision function.
f(SparseArray) - Method in class smile.base.svm.LinearKernelMachine
Returns the value of decision function.
f(T) - Method in class smile.base.rbf.RBF
The activation function.
f1 - Variable in class smile.validation.ClassificationMetrics
The F-1 score on validation data.
F1 - Static variable in class smile.validation.metric.FScore
The F_1 score, the harmonic mean of precision and recall.
F2 - Static variable in class smile.validation.metric.FScore
The F_2 score, which weighs recall higher than precision.
facet(String) - Method in class smile.plot.vega.Facet
Returns the field definition for faceting the plot by one field.
Facet - Class in smile.plot.vega
A facet is a trellis plot (or small multiple) of a series of similar plots that displays different subsets of the same data, facilitating comparison across subsets.
Facet(VegaLite) - Constructor for class smile.plot.vega.Facet
Constructor.
FacetField - Class in smile.plot.vega
Facet field definition object.
factor(int) - Method in class smile.data.measure.CategoricalMeasure
Returns the factor value (in range [0, size)) of level.
FactorCrossing - Class in smile.data.formula
Factor crossing.
FactorCrossing(int, String...) - Constructor for class smile.data.formula.FactorCrossing
Constructor.
FactorCrossing(String...) - Constructor for class smile.data.formula.FactorCrossing
Constructor.
factorial(int) - Static method in class smile.math.MathEx
The factorial of n.
FactorInteraction - Class in smile.data.formula
The interaction of all the factors appearing in the term.
FactorInteraction(String...) - Constructor for class smile.data.formula.FactorInteraction
Constructor.
factorize(String...) - Method in interface smile.data.DataFrame
Returns a new DataFrame with given columns converted to nominal.
factorize(CategoricalMeasure) - Method in interface smile.data.vector.StringVector
Converts strings to discrete measured values.
Fallout - Class in smile.validation.metric
Fall-out, false alarm rate, or false positive rate (FPR)
Fallout() - Constructor for class smile.validation.metric.Fallout
 
falseChild() - Method in class smile.base.cart.InternalNode
Returns the false branch child.
FDistribution - Class in smile.stat.distribution
F-distribution arises in the testing of whether two observed samples have the same variance.
FDistribution(int, int) - Constructor for class smile.stat.distribution.FDistribution
Constructor.
FDR - Class in smile.validation.metric
The false discovery rate (FDR) is ratio of false positives to combined true and false positives, which is actually 1 - precision.
FDR() - Constructor for class smile.validation.metric.FDR
 
feature - Variable in class smile.feature.selection.InformationValue
The feature name.
feature - Variable in class smile.feature.selection.SignalNoiseRatio
The feature name.
feature - Variable in class smile.feature.selection.SumSquaresRatio
The feature name.
feature() - Method in class smile.base.cart.InternalNode
Returns the split feature.
Feature - Interface in smile.data.formula
A feature in the formula once bound to a schema.
features - Variable in class smile.sequence.CRFLabeler
The feature function.
features() - Method in class smile.feature.extraction.BagOfWords
Returns the feature words.
features() - Method in class smile.vision.EfficientNet
Returns the feature layer block.
FHalf - Static variable in class smile.validation.metric.FScore
The F_0.5 score, which weighs recall lower than precision.
field() - Method in interface smile.data.formula.Feature
Returns the 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.
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 class smile.feature.selection.InformationValue
Calculates the information value.
fit(DataFrame, String) - Static method in class smile.feature.selection.SignalNoiseRatio
Calculates the signal noise ratio of numeric variables.
fit(DataFrame, String) - Static method in class smile.feature.selection.SumSquaresRatio
Calculates the sum squares ratio of numeric variables.
fit(DataFrame, String...) - Static method in class smile.feature.extraction.PCA
Fits principal component analysis with covariance matrix.
fit(DataFrame, String...) - Static method in class smile.feature.imputation.SimpleImputer
Fits the missing value imputation values.
fit(DataFrame, String...) - Static method in class smile.feature.transform.MaxAbsScaler
Fits the data transformation.
fit(DataFrame, String...) - Static method in class smile.feature.transform.RobustStandardizer
Fits the data transformation.
fit(DataFrame, String...) - Static method in class smile.feature.transform.Scaler
Fits the data transformation.
fit(DataFrame, String...) - Static method in class smile.feature.transform.Standardizer
Fits the data transformation.
fit(DataFrame, String, int) - Static method in class smile.feature.selection.InformationValue
Calculates the information value.
fit(DataFrame, Function<String, String[]>, int, String...) - Static method in class smile.feature.extraction.BagOfWords
Learns a vocabulary dictionary of top-k frequent tokens in the raw documents.
fit(DataFrame, Function<DataFrame, Transform>...) - Static method in interface smile.data.transform.Transform
Fits a pipeline of data transforms.
fit(DataFrame, Distance<Tuple>, int) - Static method in class smile.feature.imputation.KMedoidsImputer
Fits the missing value imputation values.
fit(DataFrame, MercerKernel<double[]>, int, double, String...) - Static method in class smile.feature.extraction.KernelPCA
Fits kernel principal component analysis.
fit(DataFrame, MercerKernel<double[]>, int, String...) - Static method in class smile.feature.extraction.KernelPCA
Fits kernel principal component analysis.
fit(Dataset<?, Integer>) - Static method in class smile.classification.ClassLabels
Fits the class label mapping.
fit(Formula, DataFrame) - Static method in class smile.classification.AdaBoost
Fits a AdaBoost model.
fit(Formula, DataFrame) - Method in interface smile.classification.DataFrameClassifier.Trainer
Fits a classification model with the default hyper-parameters.
fit(Formula, DataFrame) - Static method in class smile.classification.DecisionTree
Fits a classification tree.
fit(Formula, DataFrame) - Static method in class smile.classification.GradientTreeBoost
Fits a gradient tree boosting for classification.
fit(Formula, DataFrame) - Static method in class smile.classification.RandomForest
Fits a random forest for classification.
fit(Formula, DataFrame) - Method in interface smile.regression.DataFrameRegression.Trainer
Fits a regression model with the default hyper-parameters.
fit(Formula, DataFrame) - Static method in class smile.regression.GradientTreeBoost
Fits a gradient tree boosting for regression.
fit(Formula, DataFrame) - Static method in class smile.regression.LASSO
Fits a L1-regularized least squares model.
fit(Formula, DataFrame) - Static method in class smile.regression.OLS
Fits an ordinary least squares model.
fit(Formula, DataFrame) - Static method in class smile.regression.RandomForest
Fits a random forest for regression.
fit(Formula, DataFrame) - Static method in class smile.regression.RegressionTree
Fits a regression tree.
fit(Formula, DataFrame) - Static method in class smile.regression.RidgeRegression
Fits a ridge regression model.
fit(Formula, DataFrame, double) - Static method in class smile.regression.LASSO
Fits a L1-regularized least squares model.
fit(Formula, DataFrame, double) - Static method in class smile.regression.RidgeRegression
Fits a ridge regression model.
fit(Formula, DataFrame, double[], double[], double[]) - Static method in class smile.regression.RidgeRegression
Fits a generalized ridge regression model that minimizes a weighted least squares criterion augmented with a generalized ridge penalty:
fit(Formula, DataFrame, double, double) - Static method in class smile.regression.ElasticNet
Fits an Elastic Net model.
fit(Formula, DataFrame, double, double, double, int) - Static method in class smile.regression.ElasticNet
Fits an Elastic Net model.
fit(Formula, DataFrame, double, double, int) - Static method in class smile.regression.LASSO
Fits a L1-regularized least squares model.
fit(Formula, DataFrame, int, int, int) - Static method in class smile.regression.RegressionTree
Fits a regression tree.
fit(Formula, DataFrame, int, int, int, int) - Static method in class smile.classification.AdaBoost
Fits a AdaBoost model.
fit(Formula, DataFrame, int, int, int, int, double, double) - Static method in class smile.classification.GradientTreeBoost
Fits a gradient tree boosting for classification.
fit(Formula, DataFrame, int, int, int, int, int, double) - Static method in class smile.regression.RandomForest
Fits a random forest for regression.
fit(Formula, DataFrame, int, int, int, int, int, double, LongStream) - Static method in class smile.regression.RandomForest
Fits a random forest for regression.
fit(Formula, DataFrame, int, int, SplitRule, int, int, int, double) - Static method in class smile.classification.RandomForest
Fits a random forest for classification.
fit(Formula, DataFrame, int, int, SplitRule, int, int, int, double, int[]) - Static method in class smile.classification.RandomForest
Fits a random forest for regression.
fit(Formula, DataFrame, int, int, SplitRule, int, int, int, double, int[], LongStream) - Static method in class smile.classification.RandomForest
Fits a random forest for classification.
fit(Formula, DataFrame, String, boolean, boolean) - Static method in class smile.regression.OLS
Fits an ordinary least squares model.
fit(Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in class smile.classification.OneVersusOne
Fits a multi-class model with binary data frame classifiers.
fit(Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in class smile.classification.OneVersusRest
Fits a multi-class model with binary data frame classifiers.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.AdaBoost
Fits a AdaBoost model.
fit(Formula, DataFrame, Properties) - Method in interface smile.classification.DataFrameClassifier.Trainer
Fits a classification model.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.DecisionTree
Fits a classification tree.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.GradientTreeBoost
Fits a gradient tree boosting for classification.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.RandomForest
Fits a random forest for classification.
fit(Formula, DataFrame, Properties) - Method in interface smile.regression.DataFrameRegression.Trainer
Fits a regression model.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.ElasticNet
Fits an Elastic Net model.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.GradientTreeBoost
Fits a gradient tree boosting for regression.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.LASSO
Fits a L1-regularized least squares model.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.OLS
Fits an ordinary least squares model.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.RandomForest
Fits a random forest for regression.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.RegressionTree
Fits a regression tree.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.RidgeRegression
Fits a ridge regression model.
fit(Formula, DataFrame, Loss, int, int, int, int, double, double) - Static method in class smile.regression.GradientTreeBoost
Fits a gradient tree boosting for regression.
fit(Formula, DataFrame, SplitRule, int, int, int) - Static method in class smile.classification.DecisionTree
Fits a classification tree.
fit(Formula, DataFrame, Model) - Static method in class smile.glm.GLM
Fits the generalized linear model with IWLS (iteratively reweighted least squares).
fit(Formula, DataFrame, Model, double, int) - Static method in class smile.glm.GLM
Fits the generalized linear model with IWLS (iteratively reweighted least squares).
fit(Formula, DataFrame, Model, Properties) - Static method in class smile.glm.GLM
Fits the generalized linear model with IWLS (iteratively reweighted least squares).
fit(SparseDataset<Integer>) - Static method in class smile.classification.SparseLogisticRegression
Fits logistic regression.
fit(SparseDataset<Integer>, double, double, int) - Static method in class smile.classification.SparseLogisticRegression
Fits logistic regression.
fit(SparseDataset<Integer>, Properties) - Static method in class smile.classification.SparseLogisticRegression
Fits logistic regression.
fit(Tuple[][], int[][]) - Static method in class smile.sequence.CRF
Fits a CRF model.
fit(Tuple[][], int[][], int, int, int, int, double) - Static method in class smile.sequence.CRF
Fits a CRF model.
fit(Tuple[][], int[][], Properties) - Static method in class smile.sequence.CRF
Fits a CRF model.
fit(BaseVector<?, ?, ?>) - Static method in class smile.classification.ClassLabels
Fits the class label mapping.
fit(DifferentiableMultivariateFunction, double[][], double[], double[]) - Static method in class smile.math.LevenbergMarquardt
Fits the nonlinear least squares.
fit(DifferentiableMultivariateFunction, double[][], double[], double[], double, int) - Static method in class smile.math.LevenbergMarquardt
Fits the nonlinear least squares.
fit(DifferentiableMultivariateFunction, double[], double[], double[]) - Static method in class smile.math.LevenbergMarquardt
Fits the nonlinear least squares.
fit(DifferentiableMultivariateFunction, double[], double[], double[], double, int) - Static method in class smile.math.LevenbergMarquardt
Fits the nonlinear least squares.
fit(Matrix, int) - Static method in class smile.clustering.SpectralClustering
Spectral graph clustering.
fit(Matrix, int, int, double) - Static method in class smile.clustering.SpectralClustering
Spectral graph clustering.
fit(RNNSearch<double[], double[]>, double[][], double) - Method in class smile.neighbor.MPLSH
Fits the posteriori multiple probe algorithm.
fit(RNNSearch<double[], double[]>, double[][], double, int) - Method in class smile.neighbor.MPLSH
Fits the posteriori multiple probe algorithm.
fit(RNNSearch<double[], double[]>, double[][], double, int, double) - Method in class smile.neighbor.MPLSH
Train the posteriori multiple probe algorithm.
fit(SparseArray[], double[], int, double, double, double) - Static method in class smile.regression.SVM
Fits a linear epsilon-SVR of sparse data.
fit(SparseArray[], int) - Static method in class smile.clustering.SIB
Clustering data into k clusters up to 100 iterations.
fit(SparseArray[], int[], int, double, double) - Static method in class smile.classification.SVM
Fits a binary linear SVM.
fit(SparseArray[], int[], int, double, double, int) - Static method in class smile.classification.SVM
Fits a binary linear SVM.
fit(SparseArray[], int, int) - Static method in class smile.clustering.SIB
Clustering data into k clusters.
fit(T[]) - Method in class smile.base.svm.OCSVM
Fits 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 hyper-parameters.
fit(T[], double[], Properties) - Method in interface smile.regression.Regression.Trainer
Fits a regression model.
fit(T[], double[], RBF<T>[]) - Static method in class smile.regression.RBFNetwork
Fits 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 hyper-parameters.
fit(T[], int[], int) - Method in class smile.base.svm.LASVM
Trains the model.
fit(T[], int[], int, int, BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.classification.OneVersusOne
Fits a multi-class model with binary classifiers.
fit(T[], int[], int, int, BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.classification.OneVersusRest
Fits a multi-class model with binary classifiers.
fit(T[], int[], int, Distance<T>) - Static method in class smile.classification.KNN
Fits the K-NN classifier.
fit(T[], int[], BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.classification.OneVersusOne
Fits a multi-class model with binary classifiers.
fit(T[], int[], BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.classification.OneVersusRest
Fits a multi-class model with binary classifiers.
fit(T[], int[], Properties) - Method in interface smile.classification.Classifier.Trainer
Fits a classification model.
fit(T[], int[], RBF<T>[]) - Static method in class smile.classification.RBFNetwork
Fits 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 - Variable in class smile.validation.ClassificationMetrics
The time in milliseconds of fitting the model.
fitTime - Variable in class smile.validation.RegressionMetrics
The time in milliseconds of fitting the model.
flatten() - Method in class smile.deep.tensor.Tensor
Flattens the tensor by reshaping it into a one-dimensional tensor.
flatten(int) - Method in class smile.deep.tensor.Tensor
Flattens the tensor by reshaping it into a one-dimensional tensor.
flatten(int, int) - Method in class smile.deep.tensor.Tensor
Flattens the tensor by reshaping it into a one-dimensional tensor.
flatten(String[], String[]) - Method in class smile.plot.vega.Transform
Adds a flatten transform.
FLD - Class in smile.classification
Fisher's linear discriminant.
FLD(double[], double[][], Matrix) - Constructor for class smile.classification.FLD
Constructor.
FLD(double[], double[][], Matrix, IntSet) - Constructor for class smile.classification.FLD
Constructor.
Float - Enum constant in enum class smile.data.type.DataType.ID
Float type ID.
FLOAT_DIGITS - Static variable in class smile.math.MathEx
The number of digits (in radix base) in the mantissa.
FLOAT_EPSILON - Static variable in class smile.math.MathEx
The machine precision for the float type, which is the difference between 1 and the smallest value greater than 1 that is representable for the float type.
FLOAT_MACHEP - Static variable in class smile.math.MathEx
The largest negative integer such that 1.0 + RADIXMACHEP ≠ 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 - RADIXNEGEP ≠ 1.0, except that negeps is bounded below by -(DIGITS+3)
Float16 - Enum constant in enum class smile.deep.tensor.ScalarType
Half-precision floating-point number.
Float32 - Enum constant in enum class smile.deep.tensor.ScalarType
Single-precision floating-point number.
Float64 - Enum constant in enum class smile.deep.tensor.ScalarType
Double-precision floating-point number.
FloatArrayCellRenderer - Class in smile.swing.table
Float array renderer in JTable.
FloatArrayCellRenderer() - Constructor for class smile.swing.table.FloatArrayCellRenderer
Constructor.
FloatArrayType - Static variable in class smile.data.type.DataTypes
Float Array data type.
FloatConsumer - Interface in smile.math.matrix.fp32
Single precision matrix element stream consumer.
FloatHeapSelect - Class in smile.sort
This class tracks the smallest values seen thus far in a stream of values.
FloatHeapSelect(float[]) - Constructor for class smile.sort.FloatHeapSelect
Constructor.
FloatHeapSelect(int) - Constructor for class smile.sort.FloatHeapSelect
Constructor.
FloatObjectType - Static variable in class smile.data.type.DataTypes
Float Object data type.
FloatType - Class in smile.data.type
Float data type.
FloatType - Static variable in class smile.data.type.DataTypes
Float data type.
floatValue() - Method in class smile.deep.tensor.Tensor
Returns the float value when the tensor holds a single value.
floatVector(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
floatVector(int) - Method in class smile.data.IndexDataFrame
 
floatVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
floatVector(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
FloatVector - Interface in smile.data.vector
An immutable float vector.
floor(String) - Static method in interface smile.data.formula.Terms
The floor(x) term.
floor(Term) - Static method in interface smile.data.formula.Terms
The floor(x) term.
fold(String[], String[]) - Method in class smile.plot.vega.Transform
Adds a fold transform.
folder2Id - Static variable in interface smile.vision.ImageNet
The map from folder name to class id.
folder2Target - Static variable in interface smile.vision.ImageNet
The functor mapping folder name to class id.
folders - Static variable in interface smile.vision.ImageNet
Folder names in the same order of labels.
font(String) - Method in class smile.plot.vega.Config
Sets the default font for all text marks, titles, and labels.
FontCellEditor - Class in smile.swing.table
Font editor in JTable.
FontCellEditor() - Constructor for class smile.swing.table.FontCellEditor
Constructor.
FontCellRenderer - Class in smile.swing.table
Font renderer in JTable.
FontCellRenderer() - Constructor for class smile.swing.table.FontCellRenderer
Constructor.
FontCellRenderer(String) - Constructor for class smile.swing.table.FontCellRenderer
Constructor.
FontChooser - Class in smile.swing
The FontChooser class is a swing component for font selection with JFileChooser-like APIs.
FontChooser() - Constructor for class smile.swing.FontChooser
Constructs a FontChooser object.
FontChooser(String[]) - Constructor for class smile.swing.FontChooser
Constructs a FontChooser object using the given font size array.
forEachNonZero(int, int, DoubleConsumer) - Method in class smile.math.matrix.SparseMatrix
For each loop on non-zero elements.
forEachNonZero(int, int, FloatConsumer) - Method in class smile.math.matrix.fp32.SparseMatrix
For each loop on non-zero elements.
forEachNonZero(DoubleConsumer) - Method in class smile.math.matrix.SparseMatrix
For each loop on non-zero elements.
forecast() - Method in class smile.timeseries.AR
Returns 1-step ahead forecast.
forecast() - Method in class smile.timeseries.ARMA
Returns 1-step ahead forecast.
forecast(int) - Method in class smile.timeseries.AR
Returns l-step ahead forecast.
forecast(int) - Method in class smile.timeseries.ARMA
Returns l-step ahead forecast.
FOREST_GREEN - Static variable in interface smile.plot.swing.Palette
 
format(double) - Static method in interface smile.util.Strings
Returns the string representation of a floating number without trailing zeros.
format(double, boolean) - Static method in interface smile.util.Strings
Returns the string representation of a floating number.
format(float) - Static method in interface smile.util.Strings
Returns the string representation of a floating number without trailing zeros.
format(float, boolean) - Static method in interface smile.util.Strings
Returns the string representation of a floating number.
format(String) - Method in class smile.plot.vega.Axis
Sets the text format.
format(String) - Method in class smile.plot.vega.Data
Sets the format for parsing the data.
format(String) - Method in class smile.plot.vega.Legend
Sets the text format.
format(String, Map<String, String>) - Method in class smile.plot.vega.Data
Sets the format for parsing the data.
FormatConfig - Class in smile.plot.vega
These config properties define the default number and time formats for text marks as well as axes, headers, tooltip, and legends.
formatType(String) - Method in class smile.plot.vega.Axis
Sets the format type for labels.
formatType(String) - Method in class smile.plot.vega.Legend
Sets the format type for labels.
formula - Variable in class smile.base.cart.CART
The model formula.
formula - Variable in class smile.glm.GLM
The symbolic description of the model to be fitted.
formula() - Method in class smile.classification.AdaBoost
 
formula() - Method in interface smile.classification.DataFrameClassifier
Returns the formula associated with the model.
formula() - Method in class smile.classification.DecisionTree
Returns null if the tree is part of ensemble algorithm.
formula() - Method in class smile.classification.GradientTreeBoost
 
formula() - Method in class smile.classification.RandomForest
 
formula() - Method in interface smile.feature.importance.TreeSHAP
Returns the formula associated with the model.
formula() - Method in interface smile.regression.DataFrameRegression
Returns the model formula.
formula() - Method in class smile.regression.GradientTreeBoost
 
formula() - Method in class smile.regression.LinearModel
 
formula() - Method in class smile.regression.RandomForest
 
formula() - Method in class smile.regression.RegressionTree
Returns null if the tree is part of ensemble algorithm.
Formula - Class in smile.data.formula
The model fitting formula in a compact symbolic form.
Formula(Term, Term...) - Constructor for class smile.data.formula.Formula
Constructor.
forward(BufferedImage...) - Method in interface smile.vision.transform.Transform
Transforms images to 4-D tensor with shape [samples, channels, height, width].
forward(BufferedImage...) - Method in class smile.vision.VisionModel
Forward propagation (or forward pass) through the model.
forward(Tensor) - Method in class smile.deep.activation.GELU
 
forward(Tensor) - Method in class smile.deep.activation.GLU
 
forward(Tensor) - Method in class smile.deep.activation.HardShrink
 
forward(Tensor) - Method in class smile.deep.activation.LeakyReLU
 
forward(Tensor) - Method in class smile.deep.activation.LogSigmoid
 
forward(Tensor) - Method in class smile.deep.activation.LogSoftmax
 
forward(Tensor) - Method in class smile.deep.activation.ReLU
 
forward(Tensor) - Method in class smile.deep.activation.Sigmoid
 
forward(Tensor) - Method in class smile.deep.activation.SiLU
 
forward(Tensor) - Method in class smile.deep.activation.Softmax
 
forward(Tensor) - Method in class smile.deep.activation.SoftShrink
 
forward(Tensor) - Method in class smile.deep.activation.Tanh
 
forward(Tensor) - Method in class smile.deep.activation.TanhShrink
 
forward(Tensor) - Method in class smile.deep.layer.AdaptiveAvgPool2dLayer
 
forward(Tensor) - Method in class smile.deep.layer.AvgPool2dLayer
 
forward(Tensor) - Method in class smile.deep.layer.BatchNorm1dLayer
 
forward(Tensor) - Method in class smile.deep.layer.BatchNorm2dLayer
 
forward(Tensor) - Method in class smile.deep.layer.Conv2dLayer
 
forward(Tensor) - Method in class smile.deep.layer.DropoutLayer
 
forward(Tensor) - Method in class smile.deep.layer.EmbeddingLayer
 
forward(Tensor) - Method in class smile.deep.layer.FullyConnectedLayer
 
forward(Tensor) - Method in class smile.deep.layer.GroupNormLayer
 
forward(Tensor) - Method in interface smile.deep.layer.Layer
Forward propagation (or forward pass) through the layer.
forward(Tensor) - Method in class smile.deep.layer.MaxPool2dLayer
 
forward(Tensor) - Method in class smile.deep.layer.SequentialBlock
 
forward(Tensor) - Method in class smile.deep.Model
Forward propagation (or forward pass) through the model.
forward(Tensor) - Method in class smile.llm.PositionalEncoding
 
forward(Tensor) - Method in class smile.llm.Transformer
Forward propagation (or forward pass).
forward(Tensor) - Method in class smile.vision.EfficientNet
 
forward(Tensor) - Method in class smile.vision.layer.Conv2dNormActivation
 
forward(Tensor) - Method in class smile.vision.layer.FusedMBConv
 
forward(Tensor) - Method in class smile.vision.layer.MBConv
 
forward(Tensor) - Method in class smile.vision.layer.SqueezeExcitation
 
forward(Tensor) - Method in class smile.vision.layer.StochasticDepth
 
FPGrowth - Class in smile.association
Frequent item set mining based on the FP-growth (frequent pattern growth) algorithm, which employs an extended prefix-tree (FP-tree) structure to store the database in a compressed form.
FPTree - Class in smile.association
FP-tree data structure used in FP-growth (frequent pattern growth) algorithm for frequent item set mining.
frame(Integer, Integer) - Method in class smile.plot.vega.ImputeTransform
Sets the frame to control the window over which the specified method is applied.
frame(Integer, Integer) - Method in class smile.plot.vega.WindowTransform
Sets the frame specification indicating how the sliding window should proceed.
frame(DataFrame) - Method in class smile.data.formula.Formula
Returns a data frame of predictors and optionally response variable (if input data frame has the related variable(s)).
from(Path) - Static method in interface smile.data.BinarySparseDataset
Parse a binary sparse dataset from a file, of which each line is a data item which are the indices of nonzero elements.
from(Path) - Static method in interface smile.data.SparseDataset
Parses spare dataset in coordinate triple tuple list format.
from(Path, int) - Static method in interface smile.data.SparseDataset
Reads spare dataset in coordinate triple tuple list format.
FScore - Class in smile.validation.metric
The F-score (or F-measure) considers both the precision and the recall of the test to compute the score.
FScore() - Constructor for class smile.validation.metric.FScore
Constructor of F1 score.
FScore(double) - Constructor for class smile.validation.metric.FScore
Constructor of general F-score.
ftest() - Method in class smile.regression.LinearModel
Returns the F-statistic of goodness-of-fit.
FTest - Class in smile.stat.hypothesis
F test of the hypothesis that two independent samples come from normal distributions with the same variance, against the alternative that they come from normal distributions with different variances.
FTest(double, int, int, double) - Constructor for class smile.stat.hypothesis.FTest
Constructor.
FullyConnectedLayer - Class in smile.deep.layer
A fully connected layer with nonlinear activation function.
FullyConnectedLayer(int, int) - Constructor for class smile.deep.layer.FullyConnectedLayer
Constructor.
Function - Interface in smile.math
An interface representing a univariate real function.
FusedMBConv - Class in smile.vision.layer
Fused-MBConv replaces the depthwise-conv3Ă—3 and expansion-conv1Ă—1 in MBConv with single regular conv3Ă—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
 
generateSeed() - Static method in class smile.math.MathEx
Returns a random number to seed other random number generators.
generateSeed(int) - Static method in class smile.math.MathEx
Returns the given number of random bytes to seed other random number generators.
GeneticAlgorithm<T> - Class in smile.gap
A genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution.
GeneticAlgorithm(T[]) - Constructor for class smile.gap.GeneticAlgorithm
Constructor.
GeneticAlgorithm(T[], Selection, int) - Constructor for class smile.gap.GeneticAlgorithm
Constructor.
GeometricDistribution - Class in smile.stat.distribution
The geometric distribution is a discrete probability distribution of the number X of Bernoulli trials needed to get one success, supported on the set {1, 2, 3, …}.
GeometricDistribution(double) - Constructor for class smile.stat.distribution.GeometricDistribution
Constructor.
geqrf(Layout, int, int, double[], int, double[]) - Method in interface smile.math.blas.LAPACK
Computes a QR factorization of a general M-by-N matrix A.
geqrf(Layout, int, int, double[], int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
geqrf(Layout, int, int, float[], int, float[]) - Method in interface smile.math.blas.LAPACK
Computes a QR factorization of a general M-by-N matrix A.
geqrf(Layout, int, int, float[], int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
geqrf(Layout, int, int, DoubleBuffer, int, DoubleBuffer) - Method in interface smile.math.blas.LAPACK
Computes a QR factorization of a general M-by-N matrix A.
geqrf(Layout, int, int, DoubleBuffer, int, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
geqrf(Layout, int, int, FloatBuffer, int, FloatBuffer) - Method in interface smile.math.blas.LAPACK
Computes a QR factorization of a general M-by-N matrix A.
geqrf(Layout, int, int, FloatBuffer, int, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
geqrf(Layout, int, int, DoublePointer, int, DoublePointer) - Method in interface smile.math.blas.LAPACK
Computes a QR factorization of a general M-by-N matrix A.
geqrf(Layout, int, int, DoublePointer, int, DoublePointer) - Method in class smile.math.blas.openblas.OpenBLAS
 
ger(Layout, int, int, double, double[], int, double[], int, double[], int) - Method in interface smile.math.blas.BLAS
Performs the rank-1 update operation.
ger(Layout, int, int, double, double[], int, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
ger(Layout, int, int, double, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.BLAS
Performs the rank-1 update operation.
ger(Layout, int, int, double, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
ger(Layout, int, int, double, DoublePointer, int, DoublePointer, int, DoublePointer, int) - Method in interface smile.math.blas.BLAS
Performs the rank-1 update operation.
ger(Layout, int, int, double, DoublePointer, int, DoublePointer, int, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
ger(Layout, int, int, float, float[], int, float[], int, float[], int) - Method in interface smile.math.blas.BLAS
Performs the rank-1 update operation.
ger(Layout, int, int, float, float[], int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
ger(Layout, int, int, float, FloatBuffer, int, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.BLAS
Performs the rank-1 update operation.
ger(Layout, int, int, float, FloatBuffer, int, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesdd(Layout, SVDJob, int, int, double[], int, double[], double[], int, double[], int) - Method in interface smile.math.blas.LAPACK
Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.
gesdd(Layout, SVDJob, int, int, double[], int, double[], double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesdd(Layout, SVDJob, int, int, float[], int, float[], float[], int, float[], int) - Method in interface smile.math.blas.LAPACK
Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.
gesdd(Layout, SVDJob, int, int, float[], int, float[], float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesdd(Layout, SVDJob, int, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, int, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK
Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.
gesdd(Layout, SVDJob, int, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesdd(Layout, SVDJob, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK
Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.
gesdd(Layout, SVDJob, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesdd(Layout, SVDJob, int, int, DoublePointer, int, DoublePointer, DoublePointer, int, DoublePointer, int) - Method in interface smile.math.blas.LAPACK
Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.
gesdd(Layout, SVDJob, int, int, DoublePointer, int, DoublePointer, DoublePointer, int, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesv(Layout, int, int, double[], int, int[], double[], int) - Method in interface smile.math.blas.LAPACK
Solves a real system of linear equations.
gesv(Layout, int, int, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesv(Layout, int, int, float[], int, int[], float[], int) - Method in interface smile.math.blas.LAPACK
Solves a real system of linear equations.
gesv(Layout, int, int, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesv(Layout, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK
Solves a real system of linear equations.
gesv(Layout, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesv(Layout, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK
Solves a real system of linear equations.
gesv(Layout, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesv(Layout, int, int, DoublePointer, int, IntPointer, DoublePointer, int) - Method in interface smile.math.blas.LAPACK
Solves a real system of linear equations.
gesv(Layout, int, int, DoublePointer, int, IntPointer, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesvd(Layout, SVDJob, SVDJob, int, int, double[], int, double[], double[], int, double[], int, double[]) - Method in interface smile.math.blas.LAPACK
Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.
gesvd(Layout, SVDJob, SVDJob, int, int, double[], int, double[], double[], int, double[], int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesvd(Layout, SVDJob, SVDJob, int, int, float[], int, float[], float[], int, float[], int, float[]) - Method in interface smile.math.blas.LAPACK
Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.
gesvd(Layout, SVDJob, SVDJob, int, int, float[], int, float[], float[], int, float[], int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesvd(Layout, SVDJob, SVDJob, int, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer) - Method in interface smile.math.blas.LAPACK
Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.
gesvd(Layout, SVDJob, SVDJob, int, int, DoubleBuffer, int, DoubleBuffer, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesvd(Layout, SVDJob, SVDJob, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int, FloatBuffer, int, FloatBuffer) - Method in interface smile.math.blas.LAPACK
Computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors.
gesvd(Layout, SVDJob, SVDJob, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int, FloatBuffer, int, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
get(double[]) - Method in class smile.neighbor.lsh.Hash
Returns the bucket entry for the given point.
get(int) - Method in interface smile.data.DataFrame
Returns the row at the specified index.
get(int) - Method in interface smile.data.Dataset
Returns the instance at the specified index.
get(int) - Method in class smile.data.IndexDataFrame
 
get(int) - Method in interface smile.data.Tuple
Returns the value at position i.
get(int) - Method in interface smile.data.vector.BaseVector
Returns the value at position i, which may be null.
get(int) - Method in class smile.math.Complex.Array
Returns the i-th element.
get(int) - Method in class smile.math.matrix.fp32.SparseMatrix
Returns the element at the storage index.
get(int) - Method in class smile.math.matrix.SparseMatrix
Returns the element at the storage index.
get(int) - Method in class smile.neighbor.lsh.Hash
Returns the bucket entry for the given hash value.
get(int) - Method in class smile.sort.DoubleHeapSelect
Returns the i-th smallest value seen so far.
get(int) - Method in class smile.sort.FloatHeapSelect
Returns the i-th smallest value seen so far.
get(int) - Method in class smile.sort.HeapSelect
Returns the i-th smallest value seen so far.
get(int) - Method in class smile.sort.IntHeapSelect
Returns the i-th smallest value seen so far.
get(int) - Method in class smile.util.DoubleArrayList
Returns the value at the specified position in this list.
get(int) - Method in class smile.util.IntArrayList
Returns the value at the specified position in this list.
get(int) - Method in class smile.util.IntDoubleHashMap
Returns the value to which the specified key is mapped, or Double.NaN if this map contains no mapping for the key.
get(int) - Method in class smile.util.SparseArray
Returns the value of i-th entry.
get(int...) - Method in interface smile.data.vector.BaseVector
Returns a new vector with selected entries.
get(int...) - Method in interface smile.data.vector.BooleanVector
 
get(int...) - Method in interface smile.data.vector.ByteVector
 
get(int...) - Method in interface smile.data.vector.CharVector
 
get(int...) - Method in interface smile.data.vector.DoubleVector
 
get(int...) - Method in interface smile.data.vector.FloatVector
 
get(int...) - Method in interface smile.data.vector.IntVector
 
get(int...) - Method in interface smile.data.vector.LongVector
 
get(int...) - Method in interface smile.data.vector.ShortVector
 
get(int...) - Method in interface smile.data.vector.StringVector
 
get(int...) - Method in interface smile.data.vector.Vector
 
get(int...) - Method in class smile.deep.tensor.Tensor
Returns a portion of tensor given the indices.
get(int[], int[]) - Method in class smile.math.matrix.BigMatrix
Returns the matrix of selected rows and columns.
get(int[], int[]) - Method in class smile.math.matrix.fp32.Matrix
Returns the matrix of selected rows and columns.
get(int[], int[]) - Method in class smile.math.matrix.Matrix
Returns the matrix of selected rows and columns.
get(int, int) - Method in interface smile.data.BinarySparseDataset
Returns the binary value at entry (i, j) by binary search.
get(int, int) - Method in interface smile.data.DataFrame
Returns the cell at (i, j).
get(int, int) - Method in class smile.data.IndexDataFrame
 
get(int, int) - Method in interface smile.data.SparseDataset
Returns the value at entry (i, j).
get(int, int) - Method in class smile.math.matrix.BandMatrix
 
get(int, int) - Method in class smile.math.matrix.BigMatrix
 
get(int, int) - Method in class smile.math.matrix.fp32.BandMatrix
 
get(int, int) - Method in class smile.math.matrix.fp32.IMatrix
Returns A[i,j].
get(int, int) - Method in class smile.math.matrix.fp32.Matrix
 
get(int, int) - Method in class smile.math.matrix.fp32.SparseMatrix
 
get(int, int) - Method in class smile.math.matrix.fp32.SymmMatrix
 
get(int, int) - Method in class smile.math.matrix.IMatrix
Returns A[i,j].
get(int, int) - Method in class smile.math.matrix.Matrix
 
get(int, int) - Method in class smile.math.matrix.SparseMatrix
 
get(int, int) - Method in class smile.math.matrix.SymmMatrix
 
get(int, int) - Method in interface smile.plot.swing.Hexmap.Tooltip
Gets the tooltip of cell at (i, j).
get(int, int) - Method in class smile.util.Array2D
Returns A[i, j].
get(int, int) - Method in class smile.util.IntArray2D
Returns A[i, j].
get(int, String) - Method in interface smile.data.DataFrame
Returns the cell at (i, j).
get(long...) - Method in class smile.deep.tensor.Tensor
Returns a portion of tensor given the indices.
get(String) - Method in interface smile.data.Tuple
Returns the value by field name.
get(String) - Method in class smile.hash.PerfectHash
Returns the index of a keyword.
get(String) - Method in class smile.hash.PerfectMap
Returns the value associated with the key.
get(String) - Method in class smile.nlp.embedding.Word2Vec
Returns the embedding vector of a word.
get(String) - Static method in class smile.nlp.pos.EnglishPOSLexicon
Returns the part-of-speech tags for given word, or null if the word does not exist in the dictionary.
get(K) - Method in class smile.nlp.Trie
Returns the node of a given key.
get(K[]) - Method in class smile.nlp.Trie
Returns the associated value of a given key.
get(Index...) - Method in class smile.deep.tensor.Tensor
Returns a portion of tensor given the indices.
get(Tensor) - Method in class smile.deep.tensor.Tensor
Returns a portion of tensor given the indices.
getAbbreviation(String) - Method in interface smile.nlp.dictionary.Abbreviations
Returns the abbreviation for a word.
getAlpha() - Method in class smile.swing.AlphaIcon
Gets this AlphaIcon's opacity
getAnchor() - Method in interface smile.nlp.AnchorText
Returns the anchor text if any.
getAnchor() - Method in class smile.nlp.SimpleText
Returns the anchor text if any.
getArray(int) - Method in interface smile.data.Tuple
Returns the value at position i of array type.
getArray(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) of array type.
getArray(int, String) - Method in interface smile.data.DataFrame
Returns the field value of array type.
getArray(String) - Method in interface smile.data.Tuple
Returns the field value of array type.
getAs(int) - Method in interface smile.data.Tuple
Returns the value at position i.
getAs(String) - Method in interface smile.data.Tuple
Returns the value of a given fieldName.
getAxis(int) - Method in class smile.plot.swing.Canvas
Returns the i-th axis.
getAxisLabel(int) - Method in class smile.plot.swing.Canvas
Returns the label/legend of an axis.
getAxisLabels() - Method in class smile.plot.swing.Canvas
Returns the labels/legends of axes.
getBoolean(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive boolean.
getBoolean(int) - Method in interface smile.data.vector.BaseVector
Returns the boolean value at position i.
getBoolean(int) - Method in interface smile.data.vector.ByteVector
 
getBoolean(int) - Method in interface smile.data.vector.CharVector
 
getBoolean(int) - Method in interface smile.data.vector.DoubleVector
 
getBoolean(int) - Method in interface smile.data.vector.FloatVector
 
getBoolean(int) - Method in interface smile.data.vector.IntVector
 
getBoolean(int) - Method in interface smile.data.vector.LongVector
 
getBoolean(int) - Method in interface smile.data.vector.ShortVector
 
getBoolean(int) - Method in interface smile.data.vector.StringVector
 
getBoolean(int) - Method in interface smile.data.vector.Vector
 
getBoolean(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) as a primitive boolean.
getBoolean(int, String) - Method in interface smile.data.DataFrame
Returns the field value as a primitive boolean.
getBoolean(String) - Method in interface smile.data.Tuple
Returns the field value as a primitive boolean.
getByte(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive byte.
getByte(int) - Method in interface smile.data.vector.BaseVector
Returns the byte value at position i.
getByte(int) - Method in interface smile.data.vector.BooleanVector
 
getByte(int) - Method in interface smile.data.vector.CharVector
 
getByte(int) - Method in interface smile.data.vector.DoubleVector
 
getByte(int) - Method in interface smile.data.vector.FloatVector
 
getByte(int) - Method in interface smile.data.vector.IntVector
 
getByte(int) - Method in interface smile.data.vector.LongVector
 
getByte(int) - Method in interface smile.data.vector.ShortVector
 
getByte(int) - Method in interface smile.data.vector.StringVector
 
getByte(int) - Method in interface smile.data.vector.Vector
 
getByte(int...) - Method in class smile.deep.tensor.Tensor
Returns the byte value of element at given index.
getByte(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) as a primitive byte.
getByte(int, String) - Method in interface smile.data.DataFrame
Returns the field value as a primitive byte.
getByte(long...) - Method in class smile.deep.tensor.Tensor
Returns the byte value of element at given index.
getByte(String) - Method in interface smile.data.Tuple
Returns the field value as a primitive byte.
getCellEditor(int, int) - Method in class smile.swing.Table
 
getCellEditorValue() - Method in class smile.swing.table.ButtonCellRenderer
 
getCellEditorValue() - Method in class smile.swing.table.ColorCellEditor
 
getCellEditorValue() - Method in class smile.swing.table.DateCellEditor
 
getCellEditorValue() - Method in class smile.swing.table.DoubleArrayCellEditor
 
getCellEditorValue() - Method in class smile.swing.table.DoubleCellEditor
 
getCellEditorValue() - Method in class smile.swing.table.FontCellEditor
 
getCellEditorValue() - Method in class smile.swing.table.IntegerArrayCellEditor
 
getCellEditorValue() - Method in class smile.swing.table.IntegerCellEditor
 
getCellRenderer(int, int) - Method in class smile.swing.Table
 
getChar(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive byte.
getChar(int) - Method in interface smile.data.vector.BaseVector
Returns the character value at position i.
getChar(int) - Method in interface smile.data.vector.BooleanVector
 
getChar(int) - Method in interface smile.data.vector.ByteVector
 
getChar(int) - Method in interface smile.data.vector.DoubleVector
 
getChar(int) - Method in interface smile.data.vector.FloatVector
 
getChar(int) - Method in interface smile.data.vector.IntVector
 
getChar(int) - Method in interface smile.data.vector.LongVector
 
getChar(int) - Method in interface smile.data.vector.ShortVector
 
getChar(int) - Method in interface smile.data.vector.StringVector
 
getChar(int) - Method in interface smile.data.vector.Vector
 
getChar(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) as a primitive byte.
getChar(int, String) - Method in interface smile.data.DataFrame
Returns the field value as a primitive byte.
getChar(String) - Method in interface smile.data.Tuple
Returns the field value as a primitive byte.
getChild(K) - Method in class smile.nlp.Trie.Node
Returns the child with the key.
getChild(K[], int) - Method in class smile.nlp.Trie.Node
Returns the value matching the key sequence.
getClipNorm() - Method in class smile.base.mlp.MultilayerPerceptron
Returns the gradient clipping norm.
getClipValue() - Method in class smile.base.mlp.MultilayerPerceptron
Returns the gradient clipping value.
getColor() - Method in class smile.plot.swing.Graphics
Get the current color.
getComponentType() - Method in class smile.data.type.ArrayType
Returns the type of array elements.
getConcept(String) - Method in class smile.taxonomy.Taxonomy
Returns the concept node which synset contains the keyword.
getConcepts() - Method in class smile.taxonomy.Taxonomy
Returns all named concepts in the taxonomy.
getCoordinateSpace() - Method in class smile.plot.swing.Base
Returns the coordinates.
getDate(int) - Method in interface smile.data.Tuple
Returns the value at position i of date type as java.time.LocalDate.
getDate(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) of date type as java.time.LocalDate.
getDate(int, String) - Method in interface smile.data.DataFrame
Returns the field value of date type as java.time.LocalDate.
getDate(String) - Method in interface smile.data.Tuple
Returns the field value of date type as java.time.LocalDate.
getDateTime(int) - Method in interface smile.data.Tuple
Returns the value at position i of date type as java.time.LocalDateTime.
getDateTime(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) as java.time.LocalDateTime.
getDateTime(int, String) - Method in interface smile.data.DataFrame
Returns the field value as java.time.LocalDateTime.
getDateTime(String) - Method in interface smile.data.Tuple
Returns the field value of date type as java.time.LocalDateTime.
getDecimal(int) - Method in interface smile.data.Tuple
Returns the value at position i of decimal type as java.math.BigDecimal.
getDecimal(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) of decimal type as java.math.BigDecimal.
getDecimal(int, String) - Method in interface smile.data.DataFrame
Returns the field value of decimal type as java.math.BigDecimal.
getDecimal(String) - Method in interface smile.data.Tuple
Returns the field value of decimal type as java.math.BigDecimal.
getDefault() - Static method in class smile.nlp.pos.HMMPOSTagger
Returns the default English POS tagger.
getDegree(int) - Method in class smile.graph.AdjacencyList
 
getDegree(int) - Method in class smile.graph.AdjacencyMatrix
 
getDegree(int) - Method in interface smile.graph.Graph
Returns the degree of the specified vertex.
getDescription() - Method in class smile.swing.FileChooser.SimpleFileFilter
Returns the human-readable description of this filter.
getDimension() - Method in class smile.plot.swing.Base
Returns the dimensionality of coordinates.
getDouble(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive double.
getDouble(int) - Method in interface smile.data.vector.BaseVector
Returns the double value at position i.
getDouble(int) - Method in interface smile.data.vector.BooleanVector
 
getDouble(int) - Method in interface smile.data.vector.ByteVector
 
getDouble(int) - Method in interface smile.data.vector.CharVector
 
getDouble(int) - Method in interface smile.data.vector.FloatVector
 
getDouble(int) - Method in interface smile.data.vector.IntVector
 
getDouble(int) - Method in interface smile.data.vector.LongVector
 
getDouble(int) - Method in interface smile.data.vector.ShortVector
 
getDouble(int) - Method in interface smile.data.vector.StringVector
 
getDouble(int) - Method in interface smile.data.vector.Vector
 
getDouble(int...) - Method in class smile.deep.tensor.Tensor
Returns the double value of element at given index.
getDouble(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) as a primitive double.
getDouble(int, String) - Method in interface smile.data.DataFrame
Returns the field value as a primitive double.
getDouble(long...) - Method in class smile.deep.tensor.Tensor
Returns the double value of element at given index.
getDouble(String) - Method in interface smile.data.Tuple
Returns the field value as a primitive double.
getEdge(int, int) - Method in class smile.graph.AdjacencyList
 
getEdge(int, int) - Method in class smile.graph.AdjacencyMatrix
 
getEdge(int, int) - Method in interface smile.graph.Graph
Returns an edge connecting source vertex to target vertex if such edge exist in this graph.
getEdges() - Method in class smile.graph.AdjacencyList
 
getEdges() - Method in class smile.graph.AdjacencyMatrix
 
getEdges() - Method in interface smile.graph.Graph
Returns the edges in this graph.
getEdges(int) - Method in class smile.graph.AdjacencyList
 
getEdges(int) - Method in class smile.graph.AdjacencyMatrix
 
getEdges(int) - Method in interface smile.graph.Graph
Returns the edges from the specified vertex.
getEdges(int, int) - Method in class smile.graph.AdjacencyList
 
getEdges(int, int) - Method in class smile.graph.AdjacencyMatrix
 
getEdges(int, int) - Method in interface smile.graph.Graph
Returns the edges connecting source vertex to target vertex if such vertices exist in this graph.
getExtension(File) - Static method in class smile.swing.FileChooser
Returns the file name extension in lower case.
getExtensionLevel() - Method in class smile.anomaly.IsolationForest
Returns the extension level.
getFloat(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive float.
getFloat(int) - Method in interface smile.data.vector.BaseVector
Returns the float value at position i.
getFloat(int) - Method in interface smile.data.vector.BooleanVector
 
getFloat(int) - Method in interface smile.data.vector.ByteVector
 
getFloat(int) - Method in interface smile.data.vector.CharVector
 
getFloat(int) - Method in interface smile.data.vector.DoubleVector
 
getFloat(int) - Method in interface smile.data.vector.IntVector
 
getFloat(int) - Method in interface smile.data.vector.LongVector
 
getFloat(int) - Method in interface smile.data.vector.ShortVector
 
getFloat(int) - Method in interface smile.data.vector.StringVector
 
getFloat(int) - Method in interface smile.data.vector.Vector
 
getFloat(int...) - Method in class smile.deep.tensor.Tensor
Returns the float value of element at given index.
getFloat(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) as a primitive float.
getFloat(int, String) - Method in interface smile.data.DataFrame
Returns the field value as a primitive float.
getFloat(long...) - Method in class smile.deep.tensor.Tensor
Returns the float value of element at given index.
getFloat(String) - Method in interface smile.data.Tuple
Returns the field value as a primitive float.
getFocusBorder() - Method in class smile.swing.table.ButtonCellRenderer
Get foreground color of the button when the cell has focus
getFont() - Method in class smile.plot.swing.Graphics
Get the current font.
getFull(String) - Method in interface smile.nlp.dictionary.Abbreviations
Returns the full word of an abbreviation.
getGraphics() - Method in class smile.plot.swing.Graphics
Returns the Java2D graphics object.
getHeight() - Method in class smile.plot.swing.Dendrogram
Returns the height of tree.
getIcon() - Method in class smile.swing.AlphaIcon
Gets the icon wrapped by this AlphaIcon
getIcon(JTable, int) - Method in class smile.swing.table.DefaultTableHeaderCellRenderer
Overloaded to return an icon suitable to the primary sorted column, or null if the column is not the primary sort key.
getIcon(JTable, int) - Method in class smile.swing.table.MultiColumnSortTableHeaderCellRenderer
Overridden to return an icon suitable to a sorted column, or null if the column is unsorted.
getIconHeight() - Method in class smile.swing.AlphaIcon
Gets the height of the bounding rectangle of this AlphaIcon.
getIconWidth() - Method in class smile.swing.AlphaIcon
Gets the width of the bounding rectangle of this AlphaIcon.
getIndegree(int) - Method in class smile.graph.AdjacencyList
 
getIndegree(int) - Method in class smile.graph.AdjacencyMatrix
 
getIndegree(int) - Method in interface smile.graph.Graph
Returns the in-degree of the specified vertex.
getInitialStateProbabilities() - Method in class smile.sequence.HMM
Returns the initial state probabilities.
getInputSize() - Method in class smile.base.mlp.Layer
Returns the dimension of input vector (not including bias value).
getInstance() - Static method in interface smile.math.blas.BLAS
Creates an instance.
getInstance() - Static method in interface smile.math.blas.LAPACK
Creates an instance.
getInstance() - Static method in class smile.nlp.dictionary.EnglishPunctuations
Returns the singleton instance.
getInstance() - Static method in class smile.nlp.normalizer.SimpleNormalizer
Returns the singleton instance.
getInstance() - Static method in class smile.nlp.tokenizer.PennTreebankTokenizer
Returns the singleton instance.
getInstance() - Static method in class smile.nlp.tokenizer.SimpleParagraphSplitter
Returns the singleton instance.
getInstance() - Static method in class smile.nlp.tokenizer.SimpleSentenceSplitter
Returns the singleton instance.
getInstance() - Static method in class smile.stat.distribution.GaussianDistribution
Returns the standard normal distribution.
getInstance() - Static method in class smile.swing.FileChooser
Returns the shared file chooser instance.
getInstance() - Static method in class smile.swing.FontChooser
Returns the shared font chooser instance.
getInstance() - Static method in class smile.swing.table.DoubleCellEditor
Returns the default instance.
getInt(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive int.
getInt(int) - Method in interface smile.data.vector.BaseVector
Returns the integer value at position i.
getInt(int) - Method in interface smile.data.vector.BooleanVector
 
getInt(int) - Method in interface smile.data.vector.ByteVector
 
getInt(int) - Method in interface smile.data.vector.CharVector
 
getInt(int) - Method in interface smile.data.vector.DoubleVector
 
getInt(int) - Method in interface smile.data.vector.FloatVector
 
getInt(int) - Method in interface smile.data.vector.LongVector
 
getInt(int) - Method in interface smile.data.vector.ShortVector
 
getInt(int) - Method in interface smile.data.vector.StringVector
 
getInt(int) - Method in interface smile.data.vector.Vector
 
getInt(int...) - Method in class smile.deep.tensor.Tensor
Returns the int value of element at given index.
getInt(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) as a primitive int.
getInt(int, String) - Method in interface smile.data.DataFrame
Returns the field value as a primitive int.
getInt(long...) - Method in class smile.deep.tensor.Tensor
Returns the int value of element at given index.
getInt(String) - Method in interface smile.data.Tuple
Returns the field value as a primitive int.
getKey() - Method in class smile.nlp.Trie.Node
Returns the key.
getLabel() - Method in class smile.plot.swing.Axis
Returns the label of the axis.
getLearningRate() - Method in class smile.base.mlp.MultilayerPerceptron
Returns the learning rate.
getLearningRate() - Method in class smile.classification.LogisticRegression
Returns the learning rate of stochastic gradient descent.
getLearningRate() - Method in class smile.classification.Maxent
Returns the learning rate of stochastic gradient descent.
getLearningRate() - Method in class smile.classification.SparseLogisticRegression
Returns the learning rate of stochastic gradient descent.
getLocalSearchSteps() - Method in class smile.gap.GeneticAlgorithm
Gets the number of iterations of local search in Lamarckian algorithm.
getLong(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive long.
getLong(int) - Method in interface smile.data.vector.BaseVector
Returns the long value at position i.
getLong(int) - Method in interface smile.data.vector.BooleanVector
 
getLong(int) - Method in interface smile.data.vector.ByteVector
 
getLong(int) - Method in interface smile.data.vector.CharVector
 
getLong(int) - Method in interface smile.data.vector.DoubleVector
 
getLong(int) - Method in interface smile.data.vector.FloatVector
 
getLong(int) - Method in interface smile.data.vector.IntVector
 
getLong(int) - Method in interface smile.data.vector.ShortVector
 
getLong(int) - Method in interface smile.data.vector.StringVector
 
getLong(int) - Method in interface smile.data.vector.Vector
 
getLong(int...) - Method in class smile.deep.tensor.Tensor
Returns the long value of element at given index.
getLong(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) as a primitive long.
getLong(int, String) - Method in interface smile.data.DataFrame
Returns the field value as a primitive long.
getLong(long...) - Method in class smile.deep.tensor.Tensor
Returns the long value of element at given index.
getLong(String) - Method in interface smile.data.Tuple
Returns the field value as a primitive long.
getLowerBound() - Method in class smile.plot.swing.BarPlot
 
getLowerBound() - Method in class smile.plot.swing.BoxPlot
 
getLowerBound() - Method in class smile.plot.swing.Contour
 
getLowerBound() - Method in class smile.plot.swing.Dendrogram
 
getLowerBound() - Method in class smile.plot.swing.Graphics
Returns the lower bounds of coordinate space.
getLowerBound() - Method in class smile.plot.swing.Grid
 
getLowerBound() - Method in class smile.plot.swing.Heatmap
 
getLowerBound() - Method in class smile.plot.swing.Hexmap
 
getLowerBound() - Method in class smile.plot.swing.Histogram3D
 
getLowerBound() - Method in class smile.plot.swing.LinePlot
 
getLowerBound() - Method in class smile.plot.swing.Plot
Returns the lower bound of data.
getLowerBound() - Method in class smile.plot.swing.QQPlot
 
getLowerBound() - Method in class smile.plot.swing.ScatterPlot
 
getLowerBound() - Method in class smile.plot.swing.ScreePlot
 
getLowerBound() - Method in class smile.plot.swing.SparseMatrixPlot
 
getLowerBound() - Method in class smile.plot.swing.StaircasePlot
 
getLowerBound() - Method in class smile.plot.swing.Surface
 
getLowerBound() - Method in class smile.plot.swing.TextPlot
 
getLowerBound() - Method in class smile.plot.swing.Wireframe
 
getLowerBounds() - Method in class smile.plot.swing.Base
Returns the lower bounds.
getLowerBounds() - Method in class smile.plot.swing.Canvas
Returns the lower bounds.
getMargin() - Method in class smile.plot.swing.Canvas
Returns the size of margin, which is not used as plot area.
getMessage(String) - Method in class smile.swing.FontChooser
 
getMnemonic() - Method in class smile.swing.table.ButtonCellRenderer
 
getMomentum() - Method in class smile.base.mlp.MultilayerPerceptron
Returns the momentum factor.
getNumberFormat() - Method in class smile.swing.table.NumberCellRenderer
Returns the number format used for rendering.
getNumVertices() - Method in class smile.graph.AdjacencyList
 
getNumVertices() - Method in class smile.graph.AdjacencyMatrix
 
getNumVertices() - Method in interface smile.graph.Graph
Returns the number of vertices.
getObjectClass() - Method in class smile.data.type.ObjectType
Returns the class of objects.
getOutdegree(int) - Method in class smile.graph.AdjacencyList
 
getOutdegree(int) - Method in class smile.graph.AdjacencyMatrix
 
getOutdegree(int) - Method in interface smile.graph.Graph
Returns the out-degree of the specified vertex.
getOutputSize() - Method in class smile.base.mlp.Layer
Returns the dimension of output vector.
getPage() - Method in class smile.swing.table.PageTableModel
Returns the current page.
getPageCount() - Method in class smile.swing.table.PageTableModel
Returns the number of pages.
getPageSize() - Method in class smile.swing.table.PageTableModel
Returns the page size.
getPaint() - Method in class smile.plot.swing.Graphics
Get the current paint object.
getPathFromRoot() - Method in class smile.taxonomy.Concept
Returns the path from root to this node.
getPathToRoot() - Method in class smile.taxonomy.Concept
Returns the path from this node to the root.
getPrecisionDigits() - Method in class smile.plot.swing.Base
Returns the precision unit digits of axes.
getPrecisionUnit() - Method in class smile.plot.swing.Base
Returns the precision units of axes.
getPrinter() - Static method in class smile.swing.Printer
Returns the printer controller object.
getProbeSequence(double[], double, int) - Method in class smile.neighbor.lsh.PosterioriModel
Generate query-directed probes.
getProjection() - Method in class smile.classification.FLD
Returns the projection matrix W.
getProjection() - Method in class smile.plot.swing.Graphics
Returns the projection object.
getProjection(double) - Method in class smile.feature.extraction.PCA
Returns the projection with top principal components that contain (more than) the given percentage of variance.
getProjection(int) - Method in class smile.feature.extraction.PCA
Returns the projection with given number of principal components.
getPropertyChangeListeners() - Method in class smile.plot.swing.Canvas
Returns an array of all the listeners that were added to the PropertyChangeSupport object with addPropertyChangeListener().
getReadableImageFilter() - Static method in class smile.swing.FileChooser.SimpleFileFilter
Returns the filter for readable images.
getRealRow(int) - Method in class smile.swing.table.PageTableModel
Returns the row number of data given the row number of current page.
getRealRowCount() - Method in class smile.swing.table.PageTableModel
The subclass should implement this method to return the real number of rows in the model.
getrf(Layout, int, int, double[], int, int[]) - Method in interface smile.math.blas.LAPACK
Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.
getrf(Layout, int, int, double[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf(Layout, int, int, float[], int, int[]) - Method in interface smile.math.blas.LAPACK
Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.
getrf(Layout, int, int, float[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf(Layout, int, int, DoubleBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK
Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.
getrf(Layout, int, int, DoubleBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf(Layout, int, int, FloatBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK
Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.
getrf(Layout, int, int, FloatBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf(Layout, int, int, DoublePointer, int, IntPointer) - Method in interface smile.math.blas.LAPACK
Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.
getrf(Layout, int, int, DoublePointer, int, IntPointer) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf2(Layout, int, int, double[], int, int[]) - Method in interface smile.math.blas.LAPACK
Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.
getrf2(Layout, int, int, double[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf2(Layout, int, int, float[], int, int[]) - Method in interface smile.math.blas.LAPACK
Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.
getrf2(Layout, int, int, float[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf2(Layout, int, int, DoubleBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK
Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.
getrf2(Layout, int, int, DoubleBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf2(Layout, int, int, FloatBuffer, int, IntBuffer) - Method in interface smile.math.blas.LAPACK
Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.
getrf2(Layout, int, int, FloatBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
getRoot() - Method in class smile.taxonomy.Taxonomy
Returns the root node of taxonomy tree.
getRowCount() - Method in class smile.swing.table.PageTableModel
 
getRowCount() - Method in class smile.swing.Table.RowHeader
Delegate method to main table
getRowHeader() - Method in class smile.swing.Table
Returns a row header for this table.
getRowHeight(int) - Method in class smile.swing.Table.RowHeader
 
getrs(Layout, Transpose, int, int, double[], int, int[], double[], int) - Method in interface smile.math.blas.LAPACK
Solves a system of linear equations
getrs(Layout, Transpose, int, int, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrs(Layout, Transpose, int, int, float[], int, int[], float[], int) - Method in interface smile.math.blas.LAPACK
Solves a system of linear equations
getrs(Layout, Transpose, int, int, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrs(Layout, Transpose, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in interface smile.math.blas.LAPACK
Solves a system of linear equations
getrs(Layout, Transpose, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrs(Layout, Transpose, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in interface smile.math.blas.LAPACK
Solves a system of linear equations
getrs(Layout, Transpose, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrs(Layout, Transpose, int, int, DoublePointer, int, IntPointer, DoublePointer, int) - Method in interface smile.math.blas.LAPACK
Solves a system of linear equations
getrs(Layout, Transpose, int, int, DoublePointer, int, IntPointer, DoublePointer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
getScale(int) - Method in interface smile.data.Tuple
Returns the value at position i of NominalScale or OrdinalScale.
getScale(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) of NominalScale or OrdinalScale.
getScale(int, String) - Method in interface smile.data.DataFrame
Returns the field value of NominalScale or OrdinalScale.
getScale(String) - Method in interface smile.data.Tuple
Returns the field value of NominalScale or OrdinalScale.
getScrollableTracksViewportWidth() - Method in class smile.swing.Table
 
getSelectedFont() - Method in class smile.swing.FontChooser
Get the selected font.
getSelectedFontFamily() - Method in class smile.swing.FontChooser
Get the family name of the selected font.
getSelectedFontSize() - Method in class smile.swing.FontChooser
Get the size of the selected font.
getSelectedFontStyle() - Method in class smile.swing.FontChooser
Get the style of the selected font.
getShapes() - Method in class smile.plot.swing.Canvas
Returns the list of shapes in the canvas.
getShort(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive short.
getShort(int) - Method in interface smile.data.vector.BaseVector
Returns the short value at position i.
getShort(int) - Method in interface smile.data.vector.BooleanVector
 
getShort(int) - Method in interface smile.data.vector.ByteVector
 
getShort(int) - Method in interface smile.data.vector.CharVector
 
getShort(int) - Method in interface smile.data.vector.DoubleVector
 
getShort(int) - Method in interface smile.data.vector.FloatVector
 
getShort(int) - Method in interface smile.data.vector.IntVector
 
getShort(int) - Method in interface smile.data.vector.LongVector
 
getShort(int) - Method in interface smile.data.vector.StringVector
 
getShort(int) - Method in interface smile.data.vector.Vector
 
getShort(int...) - Method in class smile.deep.tensor.Tensor
Returns the short value of element at given index.
getShort(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) as a primitive short.
getShort(int, String) - Method in interface smile.data.DataFrame
Returns the field value as a primitive short.
getShort(long...) - Method in class smile.deep.tensor.Tensor
Returns the short value of element at given index.
getShort(String) - Method in interface smile.data.Tuple
Returns the field value as a primitive short.
getSortKey(JTable, int) - Method in class smile.swing.table.DefaultTableHeaderCellRenderer
Returns the current sort key, or null if the column is unsorted.
getStateTransitionProbabilities() - Method in class smile.sequence.HMM
Returns the state transition probabilities.
getString(int) - Method in interface smile.data.Tuple
Returns the value at position i as a String object.
getString(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) as a String object.
getString(int, String) - Method in interface smile.data.DataFrame
Returns the field value as a String object.
getString(String) - Method in interface smile.data.Tuple
Returns the field value as a String object.
getStroke() - Method in class smile.plot.swing.Graphics
Get the current stroke.
getStruct(int) - Method in interface smile.data.Tuple
Returns the value at position i of struct type.
getStruct(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) of struct type.
getStruct(int, String) - Method in interface smile.data.DataFrame
Returns the field value of struct type.
getStruct(String) - Method in interface smile.data.Tuple
Returns the field value of struct type.
getSymbolEmissionProbabilities() - Method in class smile.sequence.HMM
Returns the symbol emission probabilities.
getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.ButtonCellRenderer
 
getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.ColorCellEditor
 
getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.DateCellEditor
 
getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.DoubleArrayCellEditor
 
getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.DoubleCellEditor
 
getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.FontCellEditor
 
getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.IntegerArrayCellEditor
 
getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class smile.swing.table.IntegerCellEditor
 
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class smile.swing.table.ButtonCellRenderer
 
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class smile.swing.table.ColorCellRenderer
 
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class smile.swing.table.DefaultTableHeaderCellRenderer
Returns the default table header cell renderer.
getTestData(String...) - Static method in interface smile.util.Paths
Get the file path of a test sample dataset.
getTestDataLines(String...) - Static method in interface smile.util.Paths
Returns the reader of a test data.
getTestDataReader(String...) - Static method in interface smile.util.Paths
Returns the reader of a test data.
getTime(int) - Method in interface smile.data.Tuple
Returns the value at position i of date type as java.time.LocalTime.
getTime(int, int) - Method in interface smile.data.DataFrame
Returns the value at position (i, j) of date type as java.time.LocalTime.
getTime(int, String) - Method in interface smile.data.DataFrame
Returns the field value of date type as java.time.LocalTime.
getTime(String) - Method in interface smile.data.Tuple
Returns the field value of date type as java.time.LocalTime.
getTitle() - Method in class smile.plot.swing.Canvas
Returns the main title of canvas.
getTitleColor() - Method in class smile.plot.swing.Canvas
Returns the color for title.
getTitleFont() - Method in class smile.plot.swing.Canvas
Returns the font for title.
getToolbar() - Method in class smile.plot.swing.PlotPanel
Returns a 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 CART algorithm, Gini impurity is a measure of how often a randomly chosen element from the set would be incorrectly labeled if it were randomly labeled according to the distribution of labels in the subset.
GLM - Class in smile.glm
Generalized linear models.
GLM(Formula, String[], Model, double[], double, double, double, double[], double[], double[][]) - Constructor for class smile.glm.GLM
Constructor.
GloVe - Class in smile.nlp.embedding
Global Vectors for Word Representation.
GloVe() - Constructor for class smile.nlp.embedding.GloVe
 
GLU - Class in smile.deep.activation
Gated Linear Unit activation function.
GLU() - Constructor for class smile.deep.activation.GLU
Constructor.
GMeans - Class in smile.clustering
G-Means clustering algorithm, an extended K-Means which tries to automatically determine the number of clusters by normality test.
GMeans(double, double[][], int[]) - Constructor for class smile.clustering.GMeans
Constructor.
GOLD - Static variable in interface smile.plot.swing.Palette
 
GoodTuring - Class in smile.stat
Good–Turing frequency estimation.
GOOGLE - Enum constant in enum class smile.nlp.dictionary.EnglishStopWords
The stop words list used by Google.
gradient() - Method in class smile.base.mlp.Layer
Returns the output gradient vector.
gradientLength(double) - Method in class smile.plot.vega.Legend
Sets the length in pixels of the primary axis of a color gradient.
gradientOpacity(double) - Method in class smile.plot.vega.Legend
Sets the opacity of the color gradient.
gradientStrokeColor(String) - Method in class smile.plot.vega.Legend
Sets the color of the gradient stroke.
gradientStrokeWidth(double) - Method in class smile.plot.vega.Legend
Sets the width of the gradient stroke.
gradientThickness(double) - Method in class smile.plot.vega.Legend
Sets the thickness in pixels of the color gradient.
GradientTreeBoost - Class in smile.classification
Gradient boosting for classification.
GradientTreeBoost - Class in smile.regression
Gradient boosting for regression.
GradientTreeBoost(Formula, RegressionTree[][], double, double[]) - Constructor for class smile.classification.GradientTreeBoost
Constructor of multi-class.
GradientTreeBoost(Formula, RegressionTree[][], double, double[], IntSet) - Constructor for class smile.classification.GradientTreeBoost
Constructor of multi-class.
GradientTreeBoost(Formula, RegressionTree[], double, double, double[]) - Constructor for class smile.classification.GradientTreeBoost
Constructor of binary class.
GradientTreeBoost(Formula, RegressionTree[], double, double, double[]) - Constructor for class smile.regression.GradientTreeBoost
Constructor.
GradientTreeBoost(Formula, RegressionTree[], double, double, double[], IntSet) - Constructor for class smile.classification.GradientTreeBoost
Constructor of binary class.
graph - Variable in class smile.manifold.IsoMap
The nearest neighbor graph.
graph - Variable in class smile.manifold.LaplacianEigenmap
Nearest neighbor graph.
graph - Variable in class smile.manifold.LLE
Nearest neighbor graph.
graph - Variable in class smile.manifold.UMAP
The nearest neighbor graph.
Graph - Interface in smile.graph
A graph is an abstract representation of a set of objects where some pairs of the objects are connected by links.
Graph.Edge - Class in smile.graph
Graph edge.
Graphics - Class in smile.plot.swing
Graphics provides methods to draw graphical primitives in logical/mathematical coordinates.
Graphics(Projection) - Constructor for class smile.plot.swing.Graphics
Constructor.
GRASS_GREEN - Static variable in interface smile.plot.swing.Palette
 
GREEN - Static variable in interface smile.plot.swing.Palette
 
grid() - Method in class smile.hpo.Hyperparameters
Generates a stream of hyperparameters for grid search.
grid(boolean) - Method in class smile.plot.vega.Axis
Sets if gridlines should be included as part of the axis.
Grid - Class in smile.plot.swing
A 2D grid plot.
Grid(double[][][], Color) - Constructor for class smile.plot.swing.Grid
Constructor.
gridAlign(String) - Method in class smile.plot.vega.Legend
Sets the alignment to apply to symbol legends rows and columns.
gridCap(String) - Method in class smile.plot.vega.Axis
Sets the stroke cap for gridlines' ending style.
gridColor(String) - Method in class smile.plot.vega.Axis
Sets the color of gridlines.
gridDash(double, double) - Method in class smile.plot.vega.Axis
Sets the alternating [stroke, space] lengths for dashed gridlines.
gridOpacity(double) - Method in class smile.plot.vega.Axis
Sets the stroke opacity of grid.
gridWidth(double) - Method in class smile.plot.vega.Axis
Sets the grid width.
groupby(String...) - Method in class smile.plot.vega.ImputeTransform
Sets the data fields by which to group the values.
groupby(String...) - Method in class smile.plot.vega.LoessTransform
Sets the data fields to group by.
groupby(String...) - Method in class smile.plot.vega.PivotTransform
Sets the data fields to group by.
groupby(String...) - Method in class smile.plot.vega.QuantileTransform
Sets the data fields to group by.
groupby(String...) - Method in class smile.plot.vega.RegressionTransform
Sets the data fields to group by.
groupby(String...) - Method in class smile.plot.vega.WindowTransform
Sets the data fields for partitioning the data objects into separate windows.
GroupNormLayer - Class in smile.deep.layer
Group normalization.
GroupNormLayer(int, int) - Constructor for class smile.deep.layer.GroupNormLayer
Constructor.
GroupNormLayer(int, int, double, boolean) - Constructor for class smile.deep.layer.GroupNormLayer
Constructor.
groups() - Method in record class smile.vision.layer.Conv2dNormActivation.Options
Returns the value of the groups record component.
GrowingNeuralGas - Class in smile.vq
Growing Neural Gas.
GrowingNeuralGas(int) - Constructor for class smile.vq.GrowingNeuralGas
Constructor.
GrowingNeuralGas(int, double, double, int, int, double, double) - Constructor for class smile.vq.GrowingNeuralGas
Constructor.
gt(double) - Method in class smile.deep.tensor.Tensor
Computes element-wise greater-than comparison.
gt(int) - Method in class smile.deep.tensor.Tensor
Computes element-wise greater-than comparison.
gt(Tensor) - Method in class smile.deep.tensor.Tensor
Computes element-wise greater-than comparison.

H

H - Variable in class smile.neighbor.LSH
The size of hash table.
H - Variable in class smile.neighbor.lsh.NeighborHashValueModel
The hash values of query object.
HaarWavelet - Class in smile.wavelet
Haar wavelet.
HaarWavelet() - Constructor for class smile.wavelet.HaarWavelet
Constructor.
HadoopInput - Interface in smile.io
Static methods that return the InputStream/Reader of a HDFS/S3.
HammingDistance - Class in smile.math.distance
In information theory, the Hamming distance between two strings of equal length is the number of positions for which the corresponding symbols are different.
HammingDistance() - Constructor for class smile.math.distance.HammingDistance
Constructor.
hardShrink(int, int) - Static method in interface smile.deep.layer.Layer
Returns a fully connected layer with hard shrink activation function.
HardShrink - Class in smile.deep.activation
Hard Shrink activation function.
HardShrink() - Constructor for class smile.deep.activation.HardShrink
Constructor.
HardShrink(double) - Constructor for class smile.deep.activation.HardShrink
Constructor.
harwell(Path) - Static method in class smile.math.matrix.fp32.SparseMatrix
Reads a sparse matrix from a Harwell-Boeing Exchange Format file.
harwell(Path) - Static method in class smile.math.matrix.SparseMatrix
Reads a sparse matrix from a Harwell-Boeing Exchange Format file.
hasEdge(int, int) - Method in class smile.graph.AdjacencyList
 
hasEdge(int, int) - Method in class smile.graph.AdjacencyMatrix
 
hasEdge(int, int) - Method in interface smile.graph.Graph
Returns true if and only if this graph contains an edge going from the source vertex to the target vertex.
hash - Variable in class smile.neighbor.LSH
Hash functions.
hash(double[]) - Method in class smile.neighbor.lsh.Hash
Apply hash functions on given vector x.
hash(Hash, PrZ[]) - Method in class smile.neighbor.lsh.Probe
Returns the bucket number of the probe.
hash(T) - Method in interface smile.hash.SimHash
Return the hash code.
Hash - Class in smile.neighbor.lsh
The hash function for Euclidean spaces.
Hash(int, int, double, int) - Constructor for class smile.neighbor.lsh.Hash
Constructor.
hash128(ByteBuffer, int, int, long, long[]) - Static method in class smile.hash.MurmurHash3
128-bit MurmurHash3 for x64.
hash32(byte[], int, int, int) - Static method in class smile.hash.MurmurHash3
32-bit MurmurHash3.
hash32(String, int) - Static method in class smile.hash.MurmurHash3
32-bit MurmurHash3.
hash32(ByteBuffer, int, int, int) - Static method in interface smile.hash.MurmurHash2
32-bit MurmurHash.
hash64(ByteBuffer, int, int, long) - Static method in interface smile.hash.MurmurHash2
64-bit MurmurHash.
hashCode() - Method in class smile.association.AssociationRule
 
hashCode() - Method in class smile.association.ItemSet
 
hashCode() - Method in record class smile.data.SampleInstance
Returns a hash code value for this object.
hashCode() - Method in record class smile.deep.SampleBatch
Returns a hash code value for this object.
hashCode() - Method in record class smile.llm.llama.Message