Skip navigation links
$ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 

$

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

A

aat() - Method in class smile.math.matrix.FloatMatrix
Returns A * A'
aat() - Method in class smile.math.matrix.FloatSparseMatrix
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 - Class in smile.data.formula
The term of abs function.
Abs(Term) - Constructor for class smile.data.formula.Abs
Constructor.
abs(String) - Static method in interface smile.data.formula.Terms
Applies Math.abs.
abs(Term) - Static method in interface smile.data.formula.Terms
Applies Math.abs.
abs() - Method in class smile.math.Complex
Returns abs/modulus/magnitude.
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.
AbstractDifferentiableMultivariateFunction - Class in smile.math
An abstract implementation that uses finite differences to calculate the partial derivatives instead of providing them analytically.
AbstractDifferentiableMultivariateFunction() - Constructor for class smile.math.AbstractDifferentiableMultivariateFunction
 
AbstractDistribution - Class in smile.stat.distribution
The base class of univariate distributions.
AbstractDistribution() - Constructor for class smile.stat.distribution.AbstractDistribution
 
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.FloatConsumer
Accepts one matrix element and performs the operation on the given arguments.
accept(File) - Method in class smile.swing.FileChooser.SimpleFileFilter
 
Accuracy - Class in smile.validation
The accuracy is the proportion of true results (both true positives and true negatives) in the population.
Accuracy() - Constructor for class smile.validation.Accuracy
 
acf(double[], int) - Static method in interface smile.timeseries.TimeSeries
Autocorrelation function.
acos(String) - Static method in interface smile.data.formula.Terms
Applies Math.acos.
acos(Term) - Static method in interface smile.data.formula.Terms
Applies Math.acos.
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.
ActivationFunction - Interface in smile.base.mlp
The activation function in hidden layers.
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.
adb(Transpose, Transpose, FloatMatrix, float[]) - Method in class smile.math.matrix.FloatMatrix
Returns A * D * B, where D is a diagonal matrix.
adb(Transpose, Transpose, Matrix, double[]) - Method in class smile.math.matrix.Matrix
Returns A * D * B, where D is a diagonal matrix.
Add - Class in smile.data.formula
The term of a + b expression.
Add(Term, Term) - Constructor for class smile.data.formula.Add
Constructor.
add(Term, Term) - Static method in interface smile.data.formula.Terms
Adds two terms.
add(String, String) - Static method in interface smile.data.formula.Terms
Adds two terms.
add(Term, String) - Static method in interface smile.data.formula.Terms
Adds two terms.
add(String, Term) - Static method in interface smile.data.formula.Terms
Adds two terms.
add(String, T) - Method in class smile.hash.PerfectMap.Builder
Add a new key-value pair.
add(Complex) - Method in class smile.math.Complex
Returns this + b.
add(double[], double[]) - Static method in class smile.math.MathEx
Element-wise sum of two arrays y = x + y.
add(int, int, float) - Method in class smile.math.matrix.FloatMatrix
A[i,j] += b
add(float) - Method in class smile.math.matrix.FloatMatrix
A += b
add(int, int, float, FloatMatrix) - Method in class smile.math.matrix.FloatMatrix
Element-wise submatrix addition A[i, j] += alpha * B
add(float, FloatMatrix) - Method in class smile.math.matrix.FloatMatrix
Element-wise addition A += alpha * B
add(float, FloatMatrix, float, FloatMatrix) - Method in class smile.math.matrix.FloatMatrix
Element-wise addition C = alpha * A + beta * B
add(int, int, float, float) - Method in class smile.math.matrix.FloatMatrix
A[i,j] = alpha * A[i,j] + beta
add(int, int, float, float, FloatMatrix) - Method in class smile.math.matrix.FloatMatrix
Element-wise submatrix addition A[i, j] = alpha * A[i, j] + beta * B
add(float, float, FloatMatrix) - Method in class smile.math.matrix.FloatMatrix
Element-wise addition A = alpha * A + beta * B
add(float, float[], float[]) - Method in class smile.math.matrix.FloatMatrix
Rank-1 update A += alpha * x * y'
add(int, int, double) - Method in class smile.math.matrix.Matrix
A[i,j] += b
add(double) - Method in class smile.math.matrix.Matrix
A += b
add(int, int, double, Matrix) - Method in class smile.math.matrix.Matrix
Element-wise submatrix addition A[i, j] += alpha * B
add(double, Matrix) - Method in class smile.math.matrix.Matrix
Element-wise addition A += alpha * B
add(double, Matrix, double, Matrix) - Method in class smile.math.matrix.Matrix
Element-wise addition C = alpha * A + beta * B
add(int, int, double, double) - Method in class smile.math.matrix.Matrix
A[i,j] = alpha * A[i,j] + beta
add(int, int, double, double, Matrix) - Method in class smile.math.matrix.Matrix
Element-wise submatrix addition A[i, j] = alpha * A[i, j] + beta * B
add(double, double, Matrix) - Method in class smile.math.matrix.Matrix
Element-wise addition A = alpha * A + beta * B
add(double, double[], double[]) - Method in class smile.math.matrix.Matrix
Rank-1 update A += alpha * x * y'
add(E[]) - Method in class smile.neighbor.BKTree
Add a dataset into BK-tree.
add(Collection<E>) - Method in class smile.neighbor.BKTree
Add a dataset into BK-tree.
add(E) - Method in class smile.neighbor.BKTree
Add a datum into the BK-tree.
add(int) - Method in class smile.neighbor.lsh.Bucket
Adds a point to bucket.
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(Text) - Method in class smile.nlp.SimpleCorpus
Add a document to the corpus.
add(Shape) - Method in class smile.plot.swing.Canvas
Add a graphical shape to the canvas.
add(Plot) - Method in class smile.plot.swing.Canvas
Add a graphical shape to the canvas.
add(double...) - Method in class smile.plot.swing.Isoline
Add a point to the contour line.
add(PlotPanel) - Method in class smile.plot.swing.PlotGrid
Add a plot into the frame.
add(double) - Method in class smile.sort.DoubleHeapSelect
Assimilate a new value from the stream.
add(float) - Method in class smile.sort.FloatHeapSelect
Assimilate a new value from the stream.
add(T) - Method in class smile.sort.HeapSelect
Assimilate a new value from the stream.
add(int) - Method in class smile.sort.IntHeapSelect
Assimilate a new value from the stream.
add(double) - Method in class smile.sort.IQAgent
Assimilate a new value from the stream.
add(int, int, double) - Method in class smile.util.Array2D
 
add(Array2D) - Method in class smile.util.Array2D
 
add(double) - Method in class smile.util.Array2D
 
add(double) - Method in class smile.util.DoubleArrayList
Appends the specified value to the end of this list.
add(double[]) - Method in class smile.util.DoubleArrayList
Appends an array to the end of this list.
add(int, int, int) - Method in class smile.util.IntArray2D
 
add(IntArray2D) - Method in class smile.util.IntArray2D
 
add(int) - Method in class smile.util.IntArray2D
 
add(int) - Method in class smile.util.IntArrayList
Appends the specified value to the end of this list.
add(IntArrayList) - Method in class smile.util.IntArrayList
Appends an array to the end of this list.
add(int[]) - Method in class smile.util.IntArrayList
Appends an array 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(String, int) - Method in class smile.validation.Hyperparameters
Adds a parameter.
add(String, double) - Method in class smile.validation.Hyperparameters
Adds a parameter.
add(String, String) - Method in class smile.validation.Hyperparameters
Adds a parameter.
add(String, int[]) - Method in class smile.validation.Hyperparameters
Adds a parameter.
add(String, double[]) - Method in class smile.validation.Hyperparameters
Adds a parameter.
add(String, String[]) - Method in class smile.validation.Hyperparameters
Adds a parameter.
add(String, int, int) - Method in class smile.validation.Hyperparameters
Adds a parameter.
add(String, int, int, int) - Method in class smile.validation.Hyperparameters
Adds a parameter.
add(String, double, double) - Method in class smile.validation.Hyperparameters
Adds a parameter.
add(String, double, double, double) - Method in class smile.validation.Hyperparameters
Adds a parameter.
addAnchor(String) - Method in interface smile.nlp.AnchorText
Add a link label to the anchor text.
addAnchor(String) - Method in class smile.nlp.SimpleText
 
addChild(K[], V, int) - Method in class smile.nlp.Trie.Node
 
addChild(String) - Method in class smile.taxonomy.Concept
Add a child to this node
addChild(Concept) - Method in class smile.taxonomy.Concept
Add a child to this node
addEdge(int, int) - Method in class smile.graph.AdjacencyList
 
addEdge(int, int, double) - Method in class smile.graph.AdjacencyList
 
addEdge(int, int) - Method in class smile.graph.AdjacencyMatrix
 
addEdge(int, int, double) - 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 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
Add 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
Adjusted Mutual Information (AMI) for comparing clustering.
AdjustedMutualInformation(AdjustedMutualInformation.Method) - Constructor for class smile.validation.AdjustedMutualInformation
Constructor.
AdjustedMutualInformation.Method - Enum in smile.validation
The normalization method.
AdjustedRandIndex - Class in smile.validation
Adjusted Rand Index.
AdjustedRandIndex() - Constructor for class smile.validation.AdjustedRandIndex
 
adjustedRSquared() - Method in class smile.regression.LinearModel
Returns adjusted R2 statistic.
adjustedRSquared() - Method in class smile.timeseries.AR
Returns adjusted R2 statistic.
adjustedRSquared() - Method in class smile.timeseries.ARMA
Returns adjusted R2 statistic.
age - Variable in class smile.vq.hebb.Edge
The age of this edges.
age() - Method in class smile.vq.hebb.Neuron
Increments the age of all edges emanating from the neuron.
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.
all(boolean[]) - Static method in class smile.math.MathEx
Given a set of boolean values, are all of the values true?
allocate(long) - Static method in class smile.io.Arrow
Creates the root allocator.
alpha - Variable in class smile.stat.distribution.BetaDistribution
The shape parameter.
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.
AnchorText - Interface in smile.nlp
The anchor text is the visible, clickable text in a hyperlink.
antecedent - Variable in class smile.association.AssociationRule
Antecedent itemset.
any(boolean[]) - Static method in class smile.math.MathEx
Given a set of boolean values, is at least one of the values true?
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, FPTree) - Static method in class smile.association.ARM
Mines the association rules.
apply(FPTree) - Static method in class smile.association.FPGrowth
Mines the frequent item sets.
apply(String) - Method in interface smile.data.DataFrame
Selects column based on the column name and return it as a Column.
apply(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
apply(int) - Method in interface smile.data.Dataset
Returns the element at the specified position in this dataset.
apply(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a data object.
apply(DataFrame) - Method in interface smile.data.formula.Feature
 
apply(Tuple) - Method in class smile.data.formula.Formula
Apply the formula on a tuple to generate the model data.
apply(int) - Method in interface smile.data.Tuple
Returns the value at position i.
apply(String) - Method in interface smile.data.Tuple
Returns the value by field name.
apply(int) - Method in interface smile.data.vector.BaseVector
Returns the value at position i, which may be null.
apply(int...) - Method in interface smile.data.vector.BaseVector
Returns a new vector with selected entries.
apply(String[]) - Method in class smile.feature.Bag
Returns the bag-of-words features of a document.
apply(int, int, int, FitnessMeasure<BitString>) - Method in class smile.feature.GAFE
Genetic algorithm based feature selection for classification.
apply(Tuple) - Method in class smile.feature.SparseOneHotEncoder
Generates the compact representation of sparse binary features for given object.
apply(DataFrame) - Method in class smile.feature.SparseOneHotEncoder
Generates the compact representation of sparse binary features for a data frame.
apply(BitString, BitString) - Method in enum smile.gap.Crossover
Returns a pair of offsprings by crossovering parent chromosomes.
apply(T[]) - Method in interface smile.gap.Selection
Select a chromosome with replacement from the population based on their fitness.
apply(int) - Method in class smile.math.Complex.Array
Returns the i-th element.
apply(T, T) - Method in interface smile.math.distance.Distance
Returns the distance measure between two objects.
apply(double) - Method in interface smile.math.Function
Computes the value of the function at x.
apply(int) - Method in interface smile.math.IntFunction
Computes the value of the function at x.
apply(T, T) - Method in interface smile.math.kernel.MercerKernel
Kernel function.
apply(int, int) - Method in class smile.math.matrix.DMatrix
Returns A[i, j] for Scala users.
apply(int, int) - Method in class smile.math.matrix.SMatrix
Returns A[i, j].
apply(double...) - Method in interface smile.math.MultivariateFunction
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(String) - Method in class smile.nlp.embedding.Word2Vec
Returns the vector embedding of a word.
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(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).
applyAsBoolean(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a data object and produces an boolean-valued result.
applyAsByte(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a data object and produces an byte-valued result.
applyAsChar(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a data object and produces an char-valued result.
applyAsDouble(T) - Method in interface smile.classification.Classifier
 
applyAsDouble(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a data object and produces an double-valued result.
applyAsDouble(T, T) - Method in interface smile.math.distance.Distance
 
applyAsDouble(T, T) - Method in interface smile.math.kernel.MercerKernel
 
applyAsDouble(double[]) - Method in interface smile.math.MultivariateFunction
 
applyAsDouble(T) - Method in interface smile.regression.Regression
 
applyAsFloat(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a data object and produces an float-valued result.
applyAsFloat(T) - Method in interface smile.util.ToFloatFunction
Applies this function to the given argument.
applyAsInt(T) - Method in interface smile.classification.Classifier
 
applyAsInt(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a data object and produces an int-valued result.
applyAsLong(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a data object and produces an long-valued result.
applyAsShort(Tuple) - Method in interface smile.data.formula.Feature
Applies the term on a data object and produces an short-valued result.
AR - Class in smile.timeseries
Autoregressive model.
AR(double[], double[], double, AR.Method) - Constructor for class smile.timeseries.AR
Constructor.
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.Method - Enum in smile.timeseries
The fitting method.
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(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.
Arff(Reader) - Constructor for class smile.io.Arff
Constructor.
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.
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 - Interface in smile.math.matrix
ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems.
ARPACK.AsymmOption - Enum in smile.math.matrix
Which eigenvalues of asymmetric matrix to compute.
ARPACK.SymmOption - Enum in smile.math.matrix
Which eigenvalues of symmetric matrix to compute.
array(DataType) - Static method in class smile.data.type.DataTypes
Creates an array data type.
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(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 - 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.
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.
asin(String) - Static method in interface smile.data.formula.Terms
Applies Math.asin.
asin(Term) - Static method in interface smile.data.formula.Terms
Applies Math.asin.
AssociationRule - Class in smile.association
Association rule object.
AssociationRule(int[], int[], double, double, double, double) - Constructor for class smile.association.AssociationRule
Constructor.
asum(int, double[], int) - Method in interface smile.math.blas.BLAS
Sums the absolute values of the elements of a vector.
asum(int, float[], int) - Method in interface smile.math.blas.BLAS
Sums the absolute values of the elements of a vector.
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 class smile.math.blas.openblas.OpenBLAS
 
asum(int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
ata() - Method in class smile.math.matrix.FloatMatrix
Returns A' * A
ata() - Method in class smile.math.matrix.FloatSparseMatrix
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
Applies Math.atan.
atan(Term) - Static method in interface smile.data.formula.Terms
Applies Math.atan.
attractors - Variable in class smile.clustering.DENCLUE
The density attractor of each observation.
AUC - Class in smile.validation
The area under the curve (AUC).
AUC() - Constructor for class smile.validation.AUC
 
AverageImputation - Class in smile.imputation
Impute missing values with the average of other attributes in the instance.
AverageImputation() - Constructor for class smile.imputation.AverageImputation
Constructor.
Avro - Class in smile.io
Apache Avro is a data serialization system.
Avro(Schema) - Constructor for class smile.io.Avro
Constructor.
Avro(InputStream) - Constructor for class smile.io.Avro
Constructor.
Avro(Path) - Constructor for class smile.io.Avro
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.
Axis - Class in smile.plot.swing
This class describes an axis of a coordinate system.
Axis(Base, int) - Constructor for class smile.plot.swing.Axis
Constructor.
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, 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(double, double[], double[]) - Method in interface smile.math.blas.BLAS
Computes a constant alpha times a vector x plus a vector 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 class smile.math.blas.openblas.OpenBLAS
 
axpy(int, float, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
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.

B

B - Variable in class smile.vq.BIRCH
The branching factor of non-leaf nodes.
backpropagate(double[]) - Method in class smile.base.mlp.HiddenLayer
 
backpropagate(double[]) - Method in class smile.base.mlp.Layer
Propagates the errors back to a lower layer.
backpropagate(double[], boolean) - Method in class smile.base.mlp.MultilayerPerceptron
Propagates the errors back through the network.
backpropagate(double[]) - Method in class smile.base.mlp.OutputLayer
 
Bag - Class in smile.feature
The bag-of-words feature of text used in natural language processing and information retrieval.
Bag(String[]) - Constructor for class smile.feature.Bag
Constructor.
Bag(String[], boolean) - Constructor for class smile.feature.Bag
Constructor.
Bagging - Class in smile.sampling
Bagging (Bootstrap aggregating) is a way to improve the classification by combining classifications of randomly generated training sets.
Bagging(int[]) - Constructor for class smile.sampling.Bagging
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(int, int, int, int) - Constructor for class smile.math.matrix.BandMatrix
Constructor.
BandMatrix(int, int, int, int, double[][]) - Constructor for class smile.math.matrix.BandMatrix
Constructor.
BandMatrix.Cholesky - Class in smile.math.matrix
The Cholesky decomposition of a symmetric, positive-definite matrix.
BandMatrix.LU - Class in smile.math.matrix
The LU decomposition.
bandwidth() - Method in class smile.stat.distribution.KernelDensity
Returns the bandwidth of kernel.
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 - 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 extends java.util.stream.BaseStream<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.
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 data living in R^d.
Bernoulli - Interface in smile.glm.model
The response variable is of Bernoulli distribution.
BernoulliDistribution - Class in smile.stat.distribution
Bernoulli distribution is a discrete probability distribution, which takes value 1 with success probability p and value 0 with failure probability q = 1 - p.
BernoulliDistribution(double) - Constructor for class smile.stat.distribution.BernoulliDistribution
Constructor.
BernoulliDistribution(boolean[]) - Constructor for class smile.stat.distribution.BernoulliDistribution
Construct an Bernoulli from the given samples.
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 - Class in smile.math.special
The beta function, also called the Euler integral of the first kind.
beta(double, double) - Static method in class smile.math.special.Beta
Beta function, also called the Euler integral of the first kind.
beta - Variable in class smile.stat.distribution.BetaDistribution
The shape parameter.
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 - Interface in smile.math
The Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization problems.
bfs() - Method in class smile.graph.AdjacencyList
 
bfs(Visitor) - Method in class smile.graph.AdjacencyList
 
bfs() - Method in class smile.graph.AdjacencyMatrix
 
bfs(Visitor) - Method in class smile.graph.AdjacencyMatrix
 
bfs() - Method in interface smile.graph.Graph
Breadth-first search connected components of graph.
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.
biasUpdate - Variable in class smile.base.mlp.Layer
The bias update.
BIC() - Method in class smile.glm.GLM
Returns the BIC score.
bic - Variable in class smile.stat.distribution.DiscreteExponentialFamilyMixture
The BIC score when the distribution is fit on a sample data.
bic(double[]) - Method in class smile.stat.distribution.DiscreteMixture
BIC score of the mixture for given data.
bic - Variable in class smile.stat.distribution.ExponentialFamilyMixture
The BIC score when the distribution is fit on a sample data.
bic(double[]) - Method in class smile.stat.distribution.Mixture
The BIC score of the mixture for given 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.MultivariateMixture
BIC score of the mixture for given data.
BIC(double, int, int) - Static method in interface smile.validation.ModelSelection
Bayesian information criterion.
BiconjugateGradient - Class in smile.math.matrix
The biconjugate gradient method is an algorithm to solve systems of linear equations.
BiconjugateGradient() - Constructor for class smile.math.matrix.BiconjugateGradient
 
BicubicInterpolation - Class in smile.interpolation
Bicubic interpolation in a two-dimensional regular grid.
BicubicInterpolation(double[], double[], double[][]) - Constructor for class smile.interpolation.BicubicInterpolation
Constructor.
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(String, String) - Constructor for class smile.nlp.Bigram
Constructor.
Bigram - Class in smile.nlp.collocation
Collocations are expressions of multiple words which commonly co-occur.
Bigram(String, String, int, double) - Constructor for class smile.nlp.collocation.Bigram
Constructor.
BilinearInterpolation - Class in smile.interpolation
Bilinear interpolation in a two-dimensional regular grid.
BilinearInterpolation(double[], double[], double[][]) - Constructor for class smile.interpolation.BilinearInterpolation
Constructor.
binary(int, KernelMachine<int[]>) - Static method in class smile.base.svm.LinearKernelMachine
Creates a linear kernel machine.
BinarySparseDataset - Interface in smile.data
Binary sparse dataset.
BinarySparseGaussianKernel - Class in smile.math.kernel
The Gaussian Kernel on binary sparse data.
BinarySparseGaussianKernel(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.
BinarySparseLaplacianKernel - Class in smile.math.kernel
The Laplacian Kernel on binary sparse data.
BinarySparseLaplacianKernel(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.
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 bias 0.
BinarySparsePolynomialKernel(int, 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.
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.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(Formula, DataFrame) - Static method in class smile.classification.LogisticRegression
Fits binomial logistic regression.
binomial(Formula, DataFrame, Properties) - Static method in class smile.classification.LogisticRegression
Fits binomial logistic regression.
binomial(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(double[][], int[], double, double, int) - Static method in class smile.classification.LogisticRegression
Fits binomial logistic regression.
Binomial(double[], double, double, IntSet) - Constructor for class smile.classification.LogisticRegression.Binomial
Constructor.
binomial(int, int[][], int[]) - Static method in class smile.classification.Maxent
Learn maximum entropy classifier.
binomial(int, int[][], int[], Properties) - Static method in class smile.classification.Maxent
Learn maximum entropy classifier.
binomial(int, int[][], int[], double, double, int) - Static method in class smile.classification.Maxent
Learn maximum entropy classifier.
Binomial(double[], double, double, IntSet) - Constructor for class smile.classification.Maxent.Binomial
Constructor.
binomial(SparseDataset, int[]) - Static method in class smile.classification.SparseLogisticRegression
Fits binomial logistic regression.
binomial(SparseDataset, int[], Properties) - Static method in class smile.classification.SparseLogisticRegression
Fits binomial logistic regression.
binomial(SparseDataset, int[], double, double, int) - Static method in class smile.classification.SparseLogisticRegression
Fits binomial logistic regression.
Binomial(double[], double, double, IntSet) - Constructor for class smile.classification.SparseLogisticRegression.Binomial
Constructor.
Binomial - Interface in smile.glm.model
The response variable is of Binomial distribution.
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.
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(int, FitnessMeasure<BitString>) - Constructor for class smile.gap.BitString
Constructor.
BitString(int, FitnessMeasure<BitString>, Crossover, double, double) - Constructor for class smile.gap.BitString
Constructor.
BitString(byte[], FitnessMeasure<BitString>) - Constructor for class smile.gap.BitString
Constructor.
BitString(byte[], FitnessMeasure<BitString>, Crossover, double, double) - Constructor for class smile.gap.BitString
Constructor.
bk() - Method in class smile.math.matrix.FloatSymmMatrix
Bunch-Kaufman decomposition.
bk() - Method in class smile.math.matrix.SymmMatrix
Bunch-Kaufman decomposition.
BKTree<E> - Class in smile.neighbor
A BK-tree is a metric tree specifically adapted to discrete metric spaces.
BKTree(Metric<E>) - Constructor for class smile.neighbor.BKTree
Constructor.
BLACK - Static variable in interface smile.plot.swing.Palette
 
BLAS - Interface in smile.math.blas
Basic Linear Algebra Subprograms.
blas() - Method in enum smile.math.blas.Diag
Returns the byte value for BLAS.
blas() - Method in enum smile.math.blas.Layout
Returns the byte value for BLAS.
blas() - Method in enum smile.math.blas.Side
Returns the byte value for BLAS.
blas() - Method in enum smile.math.blas.Transpose
Returns the byte value for BLAS.
blas() - Method in enum smile.math.blas.UPLO
Returns the byte value for BLAS.
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.
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.
BooleanPattern - Static variable in interface smile.data.type.DataType
Regex for boolean.
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(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
booleanVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
booleanVector(int) - Method in class smile.data.IndexDataFrame
 
BooleanVector - Interface in smile.data.vector
An immutable boolean vector.
Bootstrap - Class in smile.validation
The bootstrap is a general tool for assessing statistical accuracy.
Bootstrap(int, int) - Constructor for class smile.validation.Bootstrap
Constructor.
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 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(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, 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[], int) - Static method in interface smile.math.Histogram
Returns the breakpoints between histogram cells for a dataset.
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 - 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.
bucket - Variable in class smile.neighbor.lsh.Bucket
The bucket id is given by the universal bucket hashing.
build(int) - Method in class smile.base.mlp.LayerBuilder
Creates a hidden layer.
build() - Method in class smile.hash.PerfectMap.Builder
Builds the perfect map.
Builder() - Constructor for class smile.hash.PerfectMap.Builder
Constructor.
Builder(Map<String, T>) - Constructor for class smile.hash.PerfectMap.Builder
Constructor.
BunchKaufman(FloatSymmMatrix, int[], int) - Constructor for class smile.math.matrix.FloatSymmMatrix.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.
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.
ByteType - Class in smile.data.type
Byte data type.
ByteType - Static variable in class smile.data.type.DataTypes
Byte data type.
byteVector(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
byteVector(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
byteVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
byteVector(int) - Method in class smile.data.IndexDataFrame
 
ByteVector - Interface in smile.data.vector
An immutable byte vector.

C

c(int...) - Static method in class smile.math.MathEx
Combines the arguments to form a vector.
c(float...) - Static method in class smile.math.MathEx
Combines the arguments to form a vector.
c(double...) - Static method in class smile.math.MathEx
Combines the arguments to form a vector.
c(String...) - Static method in class smile.math.MathEx
Combines the arguments to form a vector.
c(int[]...) - Static method in class smile.math.MathEx
Merges multiple vectors into one.
c(float[]...) - Static method in class smile.math.MathEx
Merges multiple vectors into one.
c(double[]...) - Static method in class smile.math.MathEx
Merges multiple vectors into one.
c(String[]...) - Static method in class smile.math.MathEx
Concatenates multiple vectors into one array of strings.
CADET_BLUE - Static variable in interface smile.plot.swing.Palette
 
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 - 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
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
 
CART - Class in smile.base.cart
Classification and regression tree.
CART(Formula, StructType, StructField, Node, double[]) - Constructor for class smile.base.cart.CART
Constructor.
CART(DataFrame, StructField, int, int, int, int, int[], int[][]) - Constructor for class smile.base.cart.CART
Constructor.
CategoricalEncoder - Enum 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(String...) - Constructor for class smile.data.measure.CategoricalMeasure
Constructor.
CategoricalMeasure(List<String>) - Constructor for class smile.data.measure.CategoricalMeasure
Constructor.
CategoricalMeasure(int[]) - Constructor for class smile.data.measure.CategoricalMeasure
Constructor.
CategoricalMeasure(int[], String[]) - Constructor for class smile.data.measure.CategoricalMeasure
Constructor.
cbind(int[]...) - Static method in class smile.math.MathEx
Take a sequence of vector arguments and combine by columns.
cbind(float[]...) - Static method in class smile.math.MathEx
Take a sequence of vector arguments and combine by columns.
cbind(double[]...) - Static method in class smile.math.MathEx
Take a sequence of vector arguments and combine by columns.
cbind(String[]...) - Static method in class smile.math.MathEx
Take a sequence of vector arguments and combine by columns.
cbrt(String) - Static method in interface smile.data.formula.Terms
Applies Math.cbrt.
cbrt(Term) - Static method in interface smile.data.formula.Terms
Applies Math.cbrt.
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 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
 
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
 
cdf2tiled(double) - Method in class smile.stat.distribution.TDistribution
Two-tailed cdf.
ceil(String) - Static method in interface smile.data.formula.Terms
Applies Math.ceil.
ceil(Term) - Static method in interface smile.data.formula.Terms
Applies Math.ceil.
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.
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(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
charVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
charVector(int) - Method in class smile.data.IndexDataFrame
 
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.
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.
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(BandMatrix) - Constructor for class smile.math.matrix.BandMatrix.Cholesky
Constructor.
cholesky() - Method in class smile.math.matrix.FloatBandMatrix
Cholesky decomposition for symmetric and positive definite matrix.
Cholesky(FloatBandMatrix) - Constructor for class smile.math.matrix.FloatBandMatrix.Cholesky
Constructor.
cholesky() - Method in class smile.math.matrix.FloatMatrix
Cholesky decomposition for symmetric and positive definite matrix.
cholesky(boolean) - Method in class smile.math.matrix.FloatMatrix
Cholesky decomposition for symmetric and positive definite matrix.
Cholesky(FloatMatrix) - Constructor for class smile.math.matrix.FloatMatrix.Cholesky
Constructor.
cholesky() - Method in class smile.math.matrix.FloatSymmMatrix
Cholesky decomposition for symmetric and positive definite matrix.
Cholesky(FloatSymmMatrix) - Constructor for class smile.math.matrix.FloatSymmMatrix.Cholesky
Constructor.
cholesky() - Method in class smile.math.matrix.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(Matrix) - Constructor for class smile.math.matrix.Matrix.Cholesky
Constructor.
cholesky() - Method in class smile.math.matrix.SymmMatrix
Cholesky decomposition for symmetric and positive definite matrix.
Cholesky(SymmMatrix) - Constructor for class smile.math.matrix.SymmMatrix.Cholesky
Constructor.
CholeskyOfAtA() - Method in class smile.math.matrix.FloatMatrix.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.
classification(T[], int[], BiFunction<T[], int[], Classifier<T>>) - Method in class smile.validation.Bootstrap
Runs cross validation tests.
classification(Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Method in class smile.validation.Bootstrap
Runs cross validation tests.
classification(int, T[], int[], BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.validation.Bootstrap
Runs cross validation tests.
classification(int, Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in class smile.validation.Bootstrap
Runs cross validation tests.
classification(T[], int[], BiFunction<T[], int[], Classifier<T>>) - Method in class smile.validation.CrossValidation
Runs cross validation tests.
classification(Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Method in class smile.validation.CrossValidation
Runs cross validation tests.
classification(int, T[], int[], BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.validation.CrossValidation
Runs cross validation tests.
classification(int, Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in class smile.validation.CrossValidation
Runs cross validation tests.
classification(T[], int[], BiFunction<T[], int[], Classifier<T>>) - Method in class smile.validation.GroupKFold
Runs cross validation tests.
classification(DataFrame, Function<DataFrame, DataFrameClassifier>) - Method in class smile.validation.GroupKFold
Runs cross validation tests.
classification(T[], int[], BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.validation.LOOCV
Runs leave-one-out cross validation tests.
classification(Formula, DataFrame, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in class smile.validation.LOOCV
Runs leave-one-out cross validation tests.
ClassificationMeasure - Interface in smile.validation
An abstract interface to measure the classification performance.
Classifier<T> - Interface in smile.classification
A classifier assigns an input object into one of a given number of categories.
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.
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 of the values from this list.
clear() - Method in class smile.util.IntArrayList
Removes all of the value 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.
clone(int[][]) - 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(double[][]) - Static method in class smile.math.MathEx
Deep clone a two-dimensional array.
clone() - Method in class smile.math.matrix.BandMatrix
 
clone() - Method in class smile.math.matrix.FloatBandMatrix
 
clone() - Method in class smile.math.matrix.FloatMatrix
Returns a deep copy of matrix.
clone() - Method in class smile.math.matrix.FloatSparseMatrix
 
clone() - Method in class smile.math.matrix.FloatSymmMatrix
 
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
 
close() - Method in class smile.io.Arff
 
clustering(double[][], double[][], int[], int[]) - Method in class smile.clustering.BBDTree
Given k cluster centroids, this method assigns data to nearest centroids.
ClusterMeasure - Interface in smile.validation
An abstract interface to measure the clustering performance.
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.
collect(Class<T>) - Static method in interface smile.data.DataFrame
Returns a stream collector that accumulates objects into a DataFrame.
collect() - Static method in interface smile.data.DataFrame
Returns a stream collector that accumulates tuples into a DataFrame.
colMax(int[][]) - Static method in class smile.math.MathEx
Returns the column maximum for a matrix.
colMax(double[][]) - Static method in class smile.math.MathEx
Returns the column maximum for a matrix.
colMeans(double[][]) - Static method in class smile.math.MathEx
Returns the column means for a matrix.
colMeans() - Method in class smile.math.matrix.FloatMatrix
Returns the mean of each column.
colMeans() - Method in class smile.math.matrix.Matrix
Returns the mean of each column.
colMin(int[][]) - Static method in class smile.math.MathEx
Returns the column minimum for a matrix.
colMin(double[][]) - Static method in class smile.math.MathEx
Returns the column minimum for a matrix.
colName(int) - Method in class smile.math.matrix.IMatrix
Returns the name of i-th column.
colNames() - Method in class smile.math.matrix.IMatrix
Returns the column names.
colNames(String[]) - Method in class smile.math.matrix.IMatrix
Sets the column names.
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
 
colSds(double[][]) - Static method in class smile.math.MathEx
Returns the column deviations for a matrix.
colSds() - Method in class smile.math.matrix.FloatMatrix
Returns the standard deviations of each column.
colSds() - Method in class smile.math.matrix.Matrix
Returns the standard deviations of each column.
colSums(int[][]) - Static method in class smile.math.MathEx
Returns the column sums for a matrix.
colSums(double[][]) - Static method in class smile.math.MathEx
Returns the column sums for a matrix.
colSums() - Method in class smile.math.matrix.FloatMatrix
Returns the sum of each column.
colSums() - Method in class smile.math.matrix.Matrix
Returns the sum of each column.
column(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
column(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
column(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
column(int) - Method in class smile.data.IndexDataFrame
 
columnAdded(TableColumnModelEvent) - Method in class smile.swing.table.TableColumnSettings
 
columnIndex(String) - Method in interface smile.data.DataFrame
Returns the index of a given column name.
columnIndex(String) - Method in class smile.data.IndexDataFrame
 
columnMarginChanged(ChangeEvent) - Method in class smile.swing.table.TableColumnSettings
 
columnMoved(TableColumnModelEvent) - Method in class smile.swing.table.TableColumnSettings
 
columnRemoved(TableColumnModelEvent) - Method in class smile.swing.table.TableColumnSettings
 
columnSelectionChanged(ListSelectionEvent) - Method in class smile.swing.table.TableColumnSettings
 
comparator - Static variable in class smile.base.cart.Split
 
compareTo(CentroidClustering<T, U>) - Method in class smile.clustering.CentroidClustering
 
compareTo(MEC<T>) - Method in class smile.clustering.MEC
 
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.projection.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.
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.Layer
Computes the parameter gradient and update the weights.
computeOutputGradient(double[], double) - Method in class smile.base.mlp.OutputLayer
Compute the network output gradient.
Concept - Class in smile.taxonomy
Concept is a set of synonyms, i.e.
Concept(Concept, String...) - Constructor for class smile.taxonomy.Concept
Constructor.
condition() - Method in class smile.math.matrix.FloatMatrix.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.
ConfusionMatrix - Class in smile.validation
The confusion matrix of truth and predictions.
ConfusionMatrix(int[][]) - Constructor for class smile.validation.ConfusionMatrix
Constructor.
conjugate() - Method in class smile.math.Complex
Returns the conjugate.
consequent - Variable in class smile.association.AssociationRule
Consequent itemset.
Constant - Class in smile.data.formula
A constant value in the formula.
Constant() - Constructor for class smile.data.formula.Constant
 
constant(double) - Static method in interface smile.math.TimeFunction
Returns the constant learning rate.
contains(double[][], double[]) - Static method in class smile.math.MathEx
Determines if the polygon contains the specified coordinates.
contains(double[][], double, double) - Static method in class smile.math.MathEx
Determines if the polygon contains the specified coordinates.
contains(String) - Method in interface smile.nlp.dictionary.Dictionary
Returns true if this dictionary contains the specified word.
contains(String) - Method in enum smile.nlp.dictionary.EnglishDictionary
 
contains(String) - Method in class smile.nlp.dictionary.EnglishPunctuations
 
contains(String) - Method in enum smile.nlp.dictionary.EnglishStopWords
 
contains(String) - Method in class smile.nlp.dictionary.SimpleDictionary
 
contains(int) - Method in class smile.util.IntHashSet
Returns true if this set contains the specified element.
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[][], int, boolean) - Constructor for class smile.plot.swing.Contour
Constructor.
Contour(double[][], double[]) - Constructor for class smile.plot.swing.Contour
Constructor.
Contour(double[], double[], double[][], int, boolean) - Constructor for class smile.plot.swing.Contour
Constructor.
Contour(double[], double[], double[][], double[]) - Constructor for class smile.plot.swing.Contour
Constructor.
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.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.TSNE
The coordinate matrix in embedding space.
coordinates - Variable in class smile.manifold.UMAP
The coordinate matrix in embedding space.
coordinates - Variable in class smile.mds.IsotonicMDS
The coordinates.
coordinates - Variable in class smile.mds.MDS
The principal coordinates.
coordinates - Variable in class smile.mds.SammonMapping
The coordinates.
copy(int[], int[]) - Static method in class smile.math.MathEx
Copy x into y.
copy(float[], float[]) - Static method in class smile.math.MathEx
Copy x into y.
copy(double[], double[]) - Static method in class smile.math.MathEx
Copy x into y.
copy(int[][], int[][]) - Static method in class smile.math.MathEx
Copy x into y.
copy(float[][], float[][]) - Static method in class smile.math.MathEx
Copy x into y.
copy(double[][], double[][]) - Static method in class smile.math.MathEx
Copy x into y.
cor(int[], int[]) - 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(double[], double[]) - Static method in class smile.math.MathEx
Returns the correlation coefficient between two vectors.
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[][]) - Static method in class smile.projection.PCA
Fits principal component analysis with correlation matrix.
cor - Variable in class smile.stat.hypothesis.CorTest
Correlation coefficient
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.
cos(String) - Static method in interface smile.data.formula.Terms
Applies Math.cos.
cos(Term) - Static method in interface smile.data.formula.Terms
Applies Math.cos.
cos() - Method in class smile.math.Complex
Returns the complex cosine.
cos(float[], float[]) - Static method in class smile.math.MathEx
Returns the cosine similarity.
cos(double[], double[]) - Static method in class smile.math.MathEx
Returns the cosine similarity.
cosh(String) - Static method in interface smile.data.formula.Terms
Applies Math.cosh.
cosh(Term) - Static method in interface smile.data.formula.Terms
Applies Math.cosh.
Cost - Enum in smile.base.mlp
Neural network cost function.
cost() - Method in class smile.base.mlp.OutputLayer
Returns the cost function of neural network.
count() - Method in class smile.base.cart.DecisionNode
Returns the number of node samples in each class.
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.
counter - Variable in class smile.vq.hebb.Neuron
The local counter variable (e.g.
cov(int[], int[]) - Static method in class smile.math.MathEx
Returns the covariance between two vectors.
cov(float[], float[]) - Static method in class smile.math.MathEx
Returns the covariance between two vectors.
cov(double[], double[]) - Static method in class smile.math.MathEx
Returns the covariance between two vectors.
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() - 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[], int) - Static method in interface smile.timeseries.TimeSeries
Autocovariance function.
CoverTree<E> - 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(E[], Metric<E>) - Constructor for class smile.neighbor.CoverTree
Constructor.
CoverTree(E[], Metric<E>, double) - Constructor for class smile.neighbor.CoverTree
Constructor.
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.
cross(String...) - Static method in interface smile.data.formula.Terms
Factor crossing of two or more factors.
cross(int, String...) - Static method in interface smile.data.formula.Terms
Factor crossing of two or more factors.
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 in smile.gap
The types of crossover operation.
CrossValidation - Class in smile.validation
Cross-validation is a technique for assessing how the results of a statistical analysis will generalize to an independent data set.
CrossValidation(int, int) - Constructor for class smile.validation.CrossValidation
Constructor.
CrossValidation(int, int, boolean) - Constructor for class smile.validation.CrossValidation
Constructor.
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.
csv(String) - Static method in interface smile.io.Read
Reads a 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.
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.
Currency - Static variable in interface smile.data.measure.Measure
Currency.
CURRENCY - Static variable in class smile.swing.table.NumberCellRenderer
 
CYAN - Static variable in interface smile.plot.swing.Palette
 

D

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.ChebyshevDistance
Chebyshev distance between the two arrays of type integer.
d(float[], float[]) - Static method in class smile.math.distance.ChebyshevDistance
Chebyshev distance between the two arrays of type float.
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(T, T) - Method in interface smile.math.distance.Distance
Returns the distance measure between two objects.
d(T[], T[]) - Method in class smile.math.distance.DynamicTimeWarping
 
d(int[], int[]) - Static method in class smile.math.distance.DynamicTimeWarping
Dynamic time warping without path constraints.
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(float[], float[]) - Static method in class smile.math.distance.DynamicTimeWarping
Dynamic time warping without path constraints.
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(double[], double[]) - Static method in class smile.math.distance.DynamicTimeWarping
Dynamic time warping without path constraints.
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(String, String) - Method in class smile.math.distance.EditDistance
Edit distance between two strings.
d(char[], char[]) - Method in class smile.math.distance.EditDistance
Edit distance between two strings.
d(int[], int[]) - Method in class smile.math.distance.EuclideanDistance
Euclidean distance between the two arrays of type integer.
d(float[], float[]) - Method in class smile.math.distance.EuclideanDistance
Euclidean distance between the two arrays of type float.
d(double[], double[]) - Method in class smile.math.distance.EuclideanDistance
Euclidean distance between the two arrays of type double.
d(BitSet, BitSet) - Method in class smile.math.distance.HammingDistance
 
d(byte, byte) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two bytes.
d(short, short) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two shorts.
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(byte[], byte[]) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two byte arrays.
d(short[], short[]) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two short arrays.
d(int[], int[]) - Static method in class smile.math.distance.HammingDistance
Returns Hamming distance between the two integer arrays.
d(T[], T[]) - Method in class smile.math.distance.JaccardDistance
 
d(Set<T>, Set<T>) - Static method in class smile.math.distance.JaccardDistance
Returns the Jaccard distance between sets.
d(double[], double[]) - Method in class smile.math.distance.JensenShannonDistance
 
d(int[], int[]) - Method in class smile.math.distance.LeeDistance
 
d(double[], double[]) - Method in class smile.math.distance.MahalanobisDistance
 
d(int[], int[]) - Method in class smile.math.distance.ManhattanDistance
Manhattan distance between two arrays of type integer.
d(float[], float[]) - Method in class smile.math.distance.ManhattanDistance
Manhattan distance between two arrays of type float.
d(double[], double[]) - Method in class smile.math.distance.ManhattanDistance
Manhattan distance between two arrays of type double.
d(int[], int[]) - Method in class smile.math.distance.MinkowskiDistance
Minkowski distance between the two arrays of type integer.
d(float[], float[]) - Method in class smile.math.distance.MinkowskiDistance
Minkowski distance between the two arrays of type float.
d(double[], double[]) - Method in class smile.math.distance.MinkowskiDistance
Minkowski distance between the two arrays of type double.
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 - Variable in class smile.stat.hypothesis.KSTest
Kolmogorov-Smirnov statistic
d(String, String) - Method in class smile.taxonomy.TaxonomicDistance
Compute the distance between two concepts in a taxonomy.
d(Concept, Concept) - Method in class smile.taxonomy.TaxonomicDistance
Compute the distance between two concepts in a taxonomy.
d - Variable in class smile.vq.BIRCH
The dimensionality of data.
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(String, String) - Static method in class smile.math.distance.EditDistance
Damerau-Levenshtein distance between two strings allows insertion, deletion, substitution, or transposition of characters.
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.
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
 
data - Variable in class smile.neighbor.LSH
The data objects.
DataFrame - Interface in smile.data
An immutable collection of data organized into named columns.
DataFrameClassifier - Interface in smile.classification
Classification trait on DataFrame.
DataFrameRegression - Interface in smile.regression
Regression trait on DataFrame.
Dataset<T> - Interface in smile.data
An immutable collection of data objects.
DataType - Interface in smile.data.type
The interface of data types.
DataType.ID - Enum 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 - Class in smile.data.formula
Date/time feature extractor.
Date(String, DateFeature...) - Constructor for class smile.data.formula.Date
Constructor.
date(String, DateFeature...) - Static method in interface smile.data.formula.Terms
Extracts date/time features.
date(String) - Static method in class smile.data.type.DataTypes
Date data type with customized format.
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 in smile.data.formula
The date/time features.
DatePattern - Static variable in interface smile.data.type.DataType
Regex for date.
datetime(String) - Static method in class smile.data.type.DataTypes
DateTime data type with customized format.
DateTimePattern - Static variable in interface smile.data.type.DataType
Regex for datetime.
DateTimeType - Static variable in class smile.data.type.DataTypes
DateTime data type with ISO format.
DateTimeType - Class in smile.data.type
DateTime data type.
DateTimeType(String) - Constructor for class smile.data.type.DateTimeType
Constructor.
DateType - Static variable in class smile.data.type.DataTypes
Date data type with ISO format.
DateType - Class in smile.data.type
Date data type.
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.
DBSCAN<T> - Class in smile.clustering
Density-Based Spatial Clustering of Applications with Noise.
DBSCAN(int, double, RNNSearch<T, T>, int, int[]) - Constructor for class smile.clustering.DBSCAN
Constructor.
decimal - Static variable in interface smile.util.Strings
Decimal format for floating numbers.
DecimalType - Static variable in class smile.data.type.DataTypes
Decimal data type.
DecimalType - Class in smile.data.type
Arbitrary-precision 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.
decrement() - Method in class smile.util.MutableInt
Decrement by one.
decrement(int) - Method in class smile.util.MutableInt
Decrement.
DefaultTableHeaderCellRenderer - Class in smile.swing.table
A default cell renderer for a JTableHeader.
DefaultTableHeaderCellRenderer() - Constructor for class smile.swing.table.DefaultTableHeaderCellRenderer
Constructs a DefaultTableHeaderCellRenderer.
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.
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.
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.FloatBandMatrix.Cholesky
Returns the matrix determinant
det() - Method in class smile.math.matrix.FloatBandMatrix.LU
Returns the matrix determinant
det() - Method in class smile.math.matrix.FloatMatrix.Cholesky
Returns the matrix determinant
det() - Method in class smile.math.matrix.FloatMatrix.LU
Returns the matrix determinant
det() - Method in class smile.math.matrix.FloatSymmMatrix.BunchKaufman
Returns the matrix determinant
det() - Method in class smile.math.matrix.FloatSymmMatrix.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
DeterministicAnnealing - Class in smile.clustering
Deterministic annealing clustering.
DeterministicAnnealing(double, double[][], int[]) - Constructor for class smile.clustering.DeterministicAnnealing
Constructor.
deviance() - Method in class smile.base.cart.DecisionNode
 
deviance(int[], double[]) - Static method in class smile.base.cart.DecisionNode
Returns the deviance of node.
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 - Variable in class smile.glm.GLM
The deviance = 2 * (LogLikelihood(Saturated Model) - LogLikelihood(Proposed Model)).
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.
devianceResiduals - Variable in class smile.glm.GLM
The deviance residuals.
devianceResiduals() - Method in class smile.glm.GLM
Returns the deviance residuals.
df - Variable in class smile.glm.GLM
The degrees of freedom of the residual deviance.
df() - Method in class smile.regression.LinearModel
Returns the degree-of-freedom of residual standard error.
df - Variable in class smile.stat.hypothesis.ChiSqTest
The degree of freedom of chisq-statistic.
df - Variable in class smile.stat.hypothesis.CorTest
Degree of freedom
df - Variable in class smile.stat.hypothesis.TTest
The degree of freedom of t-statistic.
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.
df - Variable in class smile.timeseries.BoxTest
The degree of freedom.
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(Visitor) - Method in class smile.graph.AdjacencyList
 
dfs() - Method in class smile.graph.AdjacencyMatrix
 
dfs(Visitor) - Method in class smile.graph.AdjacencyMatrix
 
dfs() - Method in interface smile.graph.Graph
Depth-first search connected components of graph.
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 - Enum in smile.math.blas
The flag if a triangular matrix has unit diagonal elements.
diag() - Method in class smile.math.matrix.DMatrix
Returns the diagonal elements.
diag(float[]) - Static method in class smile.math.matrix.FloatMatrix
Returns a square diagonal matrix with the elements of vector v on the main diagonal.
diag() - Method in class smile.math.matrix.FloatMatrix.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.FloatMatrix.SVD
Returns the diagonal matrix of singular values.
diag() - Method in class smile.math.matrix.FloatSparseMatrix
 
diag(double[]) - Static method in class smile.math.matrix.Matrix
Returns a square diagonal matrix with the elements of vector v on the main diagonal.
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.SMatrix
Returns the diagonal elements.
diag() - Method in class smile.math.matrix.SparseMatrix
 
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(int) - Method in class smile.graph.AdjacencyList
 
dijkstra(int) - Method in class smile.graph.AdjacencyMatrix
 
dijkstra(int, boolean) - Method in class smile.graph.AdjacencyMatrix
Calculates the shortest path by Dijkstra algorithm.
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() - Method in interface smile.graph.Graph
Calculates the all pair shortest path by Dijkstra algorithm.
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 vector space.
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.
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, 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(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.Model - Enum in smile.classification
The generation models of naive Bayes classifier.
distance(T, U) - Method in class smile.clustering.CentroidClustering
The distance function.
distance(T, T) - Method in class smile.clustering.CLARANS
 
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(int[], int[]) - Method in class smile.clustering.KModes
 
distance(double[], SparseArray) - Method in class smile.clustering.SIB
 
distance(double[], double[]) - Method in class smile.clustering.XMeans
 
Distance<T> - Interface in smile.math.distance
An interface to calculate a distance measure between two objects.
distance(int[], int[]) - Static method in class smile.math.MathEx
The Euclidean distance.
distance(float[], float[]) - Static method in class smile.math.MathEx
The Euclidean distance.
distance(double[], double[]) - Static method in class smile.math.MathEx
The Euclidean distance.
distance(SparseArray, SparseArray) - Static method in class smile.math.MathEx
The Euclidean distance.
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.
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.
distributed() - Method in interface smile.data.Dataset
Returns true if the dataset is distributed over multiple machines.
distribution - Variable in class smile.stat.distribution.DiscreteMixture.Component
The distribution of component.
Distribution - Interface in smile.stat.distribution
Probability distribution of univariate random variable.
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.
Div - Class in smile.data.formula
The term of a / b expression.
Div(Term, Term) - Constructor for class smile.data.formula.Div
Constructor.
div(Term, Term) - Static method in interface smile.data.formula.Terms
Divides two terms.
div(String, String) - 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(String, Term) - Static method in interface smile.data.formula.Terms
Divides two terms.
div(Complex) - Method in class smile.math.Complex
Returns a / b.
div(int, int, float) - Method in class smile.math.matrix.FloatMatrix
A[i,j] /= b
div(float) - Method in class smile.math.matrix.FloatMatrix
A /= b
div(int, int, float, FloatMatrix) - Method in class smile.math.matrix.FloatMatrix
Element-wise submatrix division A[i, j] /= alpha * B
div(float, FloatMatrix) - Method in class smile.math.matrix.FloatMatrix
Element-wise division A /= alpha * B
div(float, FloatMatrix, FloatMatrix) - Method in class smile.math.matrix.FloatMatrix
Element-wise division C = alpha * A / B
div(int, int, double) - Method in class smile.math.matrix.Matrix
A[i,j] /= b
div(double) - Method in class smile.math.matrix.Matrix
A /= b
div(int, int, double, Matrix) - Method in class smile.math.matrix.Matrix
Element-wise submatrix division A[i, j] /= alpha * B
div(double, Matrix) - Method in class smile.math.matrix.Matrix
Element-wise division A /= alpha * B
div(double, Matrix, Matrix) - Method in class smile.math.matrix.Matrix
Element-wise division C = alpha * A / B
div(int, int, double) - Method in class smile.util.Array2D
 
div(Array2D) - Method in class smile.util.Array2D
 
div(double) - Method in class smile.util.Array2D
 
div(int, int, int) - Method in class smile.util.IntArray2D
 
div(IntArray2D) - Method in class smile.util.IntArray2D
 
div(int) - Method in class smile.util.IntArray2D
 
dlink(double) - Method in interface smile.glm.model.Model
The derivative of link function.
DMatrix - Class in smile.math.matrix
Double precision matrix base class.
DMatrix() - Constructor for class smile.math.matrix.DMatrix
 
dot() - Method in class smile.base.cart.CART
Returns the graphic representation in Graphviz dot format.
dot(StructType, StructField, int) - Method in class smile.base.cart.DecisionNode
 
dot(StructType, StructField, int) - Method in interface smile.base.cart.Node
Returns a dot representation for visualization.
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() - 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(int, double[], int, double[], int) - Method in interface smile.math.blas.BLAS
Computes the dot product of two vectors.
dot(int, float[], int, float[], int) - Method in interface smile.math.blas.BLAS
Computes the dot product of two vectors.
dot(double[], double[]) - Method in interface smile.math.blas.BLAS
Computes the dot product of two vectors.
dot(float[], float[]) - 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 class smile.math.blas.openblas.OpenBLAS
 
dot(int[], int[]) - Static method in class smile.math.MathEx
Returns the dot product between two vectors.
dot(float[], float[]) - Static method in class smile.math.MathEx
Returns the dot product between two vectors.
dot(double[], double[]) - Static method in class smile.math.MathEx
Returns the dot product between two vectors.
dot(SparseArray, SparseArray) - Static method in class smile.math.MathEx
Returns the dot product between two sparse arrays.
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(int) - Constructor for class smile.util.DoubleArrayList
Constructs an empty list with the specified initial capacity.
DoubleArrayList(double[]) - Constructor for class smile.util.DoubleArrayList
Constructs a list containing the values of the specified array.
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(int) - Constructor for class smile.sort.DoubleHeapSelect
Constructor.
DoubleHeapSelect(double[]) - Constructor for class smile.sort.DoubleHeapSelect
Constructor.
DoubleObjectType - Static variable in class smile.data.type.DataTypes
Double Object data type.
DoublePattern - Static variable in interface smile.data.type.DataType
Regex for double.
DoubleType - Static variable in class smile.data.type.DataTypes
Double data type.
DoubleType - Class in smile.data.type
Double data type.
doubleVector(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
doubleVector(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
doubleVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
doubleVector(int) - Method in class smile.data.IndexDataFrame
 
DoubleVector - Interface in smile.data.vector
An immutable double vector.
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(double...) - Method in class smile.plot.swing.Graphics
Draw a dot.
drawPoint(char, double...) - Method in class smile.plot.swing.Graphics
Draw a dot with given pattern.
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 given column indices.
drop(String...) - Method in interface smile.data.DataFrame
Returns a new DataFrame without given column names.
drop(int...) - Method in class smile.data.IndexDataFrame
 
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(int, int, double) - Constructor for class smile.graph.Graph.Edge
Constructor.
Edge - Class in smile.vq.hebb
The connection between neurons.
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, boolean) - 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.
eigen(DMatrix, ARPACK.AsymmOption, int) - Static method in interface smile.math.matrix.ARPACK
Computes NEV eigenvalues of an asymmetric double precision matrix.
eigen(DMatrix, ARPACK.AsymmOption, int, int, double) - Static method in interface smile.math.matrix.ARPACK
Computes NEV eigenvalues of an asymmetric double precision matrix.
eigen(SMatrix, ARPACK.AsymmOption, int) - Static method in interface smile.math.matrix.ARPACK
Computes NEV eigenvalues of an asymmetric single precision matrix.
eigen(SMatrix, ARPACK.AsymmOption, int, int, float) - Static method in interface smile.math.matrix.ARPACK
Computes NEV eigenvalues of an asymmetric single precision matrix.
eigen() - Method in class smile.math.matrix.FloatMatrix
Eigenvalue Decomposition.
eigen(boolean, boolean, boolean) - Method in class smile.math.matrix.FloatMatrix
Eigenvalue Decomposition.
eigen(DMatrix, int) - Static method in class smile.math.matrix.Lanczos
Find k largest approximate eigen pairs of a symmetric matrix by the Lanczos algorithm.
eigen(DMatrix, 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() - Method in class smile.math.matrix.Matrix
Eigenvalue Decomposition.
eigen(boolean, boolean, boolean) - Method in class smile.math.matrix.Matrix
Eigenvalue Decomposition.
eigen(DMatrix, double[]) - Static method in class smile.math.matrix.PowerIteration
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(DMatrix, double[], double, double, int) - Static method in class smile.math.matrix.PowerIteration
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.
EigenRange - Enum in smile.math.blas
THe option of eigenvalue range.
ElasticNet - Class in smile.regression
Elastic Net regularization.
ElasticNet() - Constructor for class smile.regression.ElasticNet
 
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() - Method in class smile.util.PriorityQueue
Returns true if the queue is empty.
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 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 in smile.nlp.dictionary
Several sets of English stop words.
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(double[]) - Static method in class smile.math.MathEx
Shannon's entropy.
entropy() - Method in class smile.stat.distribution.BernoulliDistribution
 
entropy() - Method in class smile.stat.distribution.BetaDistribution
 
entropy() - Method in class smile.stat.distribution.BinomialDistribution
 
entropy() - Method in class smile.stat.distribution.ChiSquareDistribution
 
entropy() - Method in class smile.stat.distribution.DiscreteMixture
Shannon entropy.
entropy() - Method in interface smile.stat.distribution.Distribution
Shannon entropy of the distribution.
entropy() - Method in class smile.stat.distribution.EmpiricalDistribution
 
entropy() - Method in class smile.stat.distribution.ExponentialDistribution
 
entropy() - Method in class smile.stat.distribution.FDistribution
Shannon entropy.
entropy() - Method in class smile.stat.distribution.GammaDistribution
 
entropy() - Method in class smile.stat.distribution.GaussianDistribution
 
entropy() - Method in class smile.stat.distribution.GeometricDistribution
Shannon entropy.
entropy() - Method in class smile.stat.distribution.HyperGeometricDistribution
 
entropy() - Method in class smile.stat.distribution.KernelDensity
Shannon entropy.
entropy() - Method in class smile.stat.distribution.LogisticDistribution
 
entropy() - Method in class smile.stat.distribution.LogNormalDistribution
 
entropy() - Method in class smile.stat.distribution.Mixture
Shannon entropy.
entropy() - Method in interface smile.stat.distribution.MultivariateDistribution
Shannon entropy of the distribution.
entropy() - Method in class smile.stat.distribution.MultivariateGaussianDistribution
 
entropy() - Method in class smile.stat.distribution.MultivariateMixture
Shannon entropy.
entropy() - Method in class smile.stat.distribution.NegativeBinomialDistribution
Shannon entropy.
entropy() - Method in class smile.stat.distribution.PoissonDistribution
 
entropy() - Method in class smile.stat.distribution.ShiftedGeometricDistribution
 
entropy() - Method in class smile.stat.distribution.TDistribution
 
entropy() - Method in class smile.stat.distribution.WeibullDistribution
 
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 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.
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 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 class smile.math.Complex
 
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.
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.
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.
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.
equals(Object) - Method in class smile.math.matrix.BandMatrix
 
equals(BandMatrix, double) - Method in class smile.math.matrix.BandMatrix
Returns if two matrices equals given an error margin.
equals(Object) - Method in class smile.math.matrix.FloatBandMatrix
 
equals(FloatBandMatrix, float) - Method in class smile.math.matrix.FloatBandMatrix
Returns if two matrices equals given an error margin.
equals(Object) - Method in class smile.math.matrix.FloatMatrix
 
equals(FloatMatrix, float) - Method in class smile.math.matrix.FloatMatrix
Returns if two matrices equals given an error margin.
equals(Object) - Method in class smile.math.matrix.FloatSymmMatrix
 
equals(FloatSymmMatrix, float) - Method in class smile.math.matrix.FloatSymmMatrix
Returns if two matrices equals given an error margin.
equals(Object) - Method in class smile.math.matrix.Matrix
 
equals(Matrix, double) - Method in class smile.math.matrix.Matrix
Returns if two matrices equals given an error margin.
equals(Object) - Method in class smile.math.matrix.SymmMatrix
 
equals(SymmMatrix, double) - Method in class smile.math.matrix.SymmMatrix
Returns if two matrices equals given an error margin.
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 class smile.util.IntPair
 
Erf - Class in smile.math.special
The error function.
erf(double) - Static method in class smile.math.special.Erf
The Gauss error function.
erfc(double) - Static method in class smile.math.special.Erf
The complementary error function.
erfcc(double) - Static method in class smile.math.special.Erf
The complementary error function with fractional error everywhere less than 1.2 × 10-7.
error() - Method in class smile.classification.RandomForest
Returns the out-of-bag estimation of error rate.
error() - Method in class smile.regression.LinearModel
Returns the residual standard error.
error() - Method in class smile.regression.RandomForest
Returns the out-of-bag estimation of RMSE.
Error - Class in smile.validation
The number of errors in the population.
Error() - Constructor for class smile.validation.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.
EVD(float[], FloatMatrix) - Constructor for class smile.math.matrix.FloatMatrix.EVD
Constructor.
EVD(float[], float[], FloatMatrix, FloatMatrix) - Constructor for class smile.math.matrix.FloatMatrix.EVD
Constructor.
EVD(double[], Matrix) - Constructor for class smile.math.matrix.Matrix.EVD
Constructor.
EVD(double[], double[], Matrix, Matrix) - Constructor for class smile.math.matrix.Matrix.EVD
Constructor.
EVDJob - Enum in smile.math.blas
The option if computing eigen vectors.
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.
evolve() - Method in interface smile.gap.LamarckianChromosome
Performs a step of (hill-climbing) local search to evolve this chromosome.
exp(String) - Static method in interface smile.data.formula.Terms
Applies Math.exp.
exp(Term) - Static method in interface smile.data.formula.Terms
Applies Math.exp.
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 initLearningRate * exp(-t / decaySteps).
exp(double, int, double) - Static method in interface smile.math.TimeFunction
Returns the exponential decay function initLearningRate * pow(endLearningRate / initLearningRate, min(t, decaySteps) / decaySteps).
exp(double, int, double, boolean) - Static method in interface smile.math.TimeFunction
Returns the exponential decay function initLearningRate * pow(decayRate, t / decaySteps).
Exp - Class in smile.projection.ica
The contrast function when the independent components are highly super-Gaussian, or when robustness is very important.
Exp() - Constructor for class smile.projection.ica.Exp
 
expand(StructType) - Method in class smile.data.formula.Formula
Expands the Dot and FactorCrossing terms on the given schema.
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.
expm1(String) - Static method in interface smile.data.formula.Terms
Applies Math.expm1.
expm1(Term) - Static method in interface smile.data.formula.Terms
Applies Math.expm1.
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(int) - Method in class smile.plot.swing.Base
Rounds the bounds for axis i.
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.
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.
eye(int) - Static method in class smile.math.matrix.FloatMatrix
Returns an n-by-n identity matrix.
eye(int, int) - Static method in class smile.math.matrix.FloatMatrix
Returns an m-by-n identity matrix.
eye(int) - Static method in class smile.math.matrix.Matrix
Returns an n-by-n identity matrix.
eye(int, int) - Static method in class smile.math.matrix.Matrix
Returns an m-by-n identity matrix.

F

f(double[]) - Method in interface smile.base.mlp.ActivationFunction
The output function.
f(double[]) - Method in class smile.base.mlp.HiddenLayer
 
f(double[]) - Method in class smile.base.mlp.Layer
The activation or output function.
f(double[]) - Method in enum smile.base.mlp.OutputFunction
The output function.
f(double[]) - Method in class smile.base.mlp.OutputLayer
 
f(T) - Method in class smile.base.rbf.RBF
The activation function.
f(T) - Method in class smile.base.svm.KernelMachine
Returns the decision function value.
f(double[]) - Method in class smile.base.svm.LinearKernelMachine
Returns the value of decision function.
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 interface smile.classification.Classifier
Returns the real-valued decision function value.
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(int) - Method in interface smile.math.IntFunction
Computes the value of the function at x.
f(double[]) - Method in interface smile.math.MultivariateFunction
Computes the value of the function at x.
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.projection.ica.Exp
 
f(double) - Method in class smile.projection.ica.Kurtosis
 
f(double) - Method in class smile.projection.ica.LogCosh
 
f - Variable in class smile.stat.hypothesis.FTest
f-statistic
factor(int) - Method in class smile.data.measure.CategoricalMeasure
Returns the factor value (in range [0, size)) of level.
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
Fall-out, false alarm rate, or false positive rate (FPR)
Fallout() - Constructor for class smile.validation.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
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.FDR
 
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.
FeatureRanking - Interface in smile.feature
Univariate feature ranking metric.
features - Variable in class smile.sequence.CRFLabeler
The feature function.
FeatureTransform - Interface in smile.feature
Feature transformation.
field() - Method in interface smile.data.formula.Feature
Returns the meta data of feature.
field(String) - Method in class smile.data.type.StructType
Return the field of given name.
field(int) - Method in class smile.data.type.StructType
Return the field at position i.
field() - Method in interface smile.data.vector.BaseVector
Returns a struct field corresponding to this vector.
fieldIndex(String) - Method in interface smile.data.Tuple
Returns the index of a given field name.
fieldIndex(String) - Method in class smile.data.type.StructType
Returns the index of a field.
fieldName(int) - Method in class smile.data.type.StructType
Returns the name of a field.
fields() - Method in class smile.data.type.StructType
Returns the 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(float) - Method in class smile.math.matrix.FloatMatrix
Fill the matrix with a value.
fill(double) - Method in class smile.math.matrix.Matrix
Fill the matrix with a value.
fill(char, int) - Static method in interface smile.util.Strings
Returns a string with a single repeated character to a specific length.
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.
find(Function, double, double, double, int) - Static method in interface smile.math.Root
Brent's method for root-finding.
find(DifferentiableFunction, double, double, double, int) - Static method in interface smile.math.Root
Newton's method (also known as the Newton–Raphson method).
findBestSplit(LeafNode, int, int, boolean[]) - Method in class smile.base.cart.CART
Finds the best attribute to split on a set of samples.
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
 
fit(double[][], int) - Static method in class smile.base.rbf.RBF
Learns Gaussian RBF function and centers from data.
fit(double[][], int, int) - Static method in class smile.base.rbf.RBF
Learns Gaussian RBF function and centers from data.
fit(double[][], int, double) - Static method in class smile.base.rbf.RBF
Learns Gaussian RBF function and centers from data.
fit(T[], Metric<T>, int) - Static method in class smile.base.rbf.RBF
Learns Gaussian RBF function and centers from data.
fit(T[], Metric<T>, int, int) - Static method in class smile.base.rbf.RBF
Learns Gaussian RBF function and centers from data.
fit(T[], Metric<T>, int, double) - Static method in class smile.base.rbf.RBF
Learns Gaussian RBF function and centers from data.
fit(T[], int[]) - Method in class smile.base.svm.LASVM
Trains the model.
fit(T[], int[], int) - Method in class smile.base.svm.LASVM
Trains the model.
fit(T[], double[]) - Method in class smile.base.svm.SVR
Fits a epsilon support vector regression model.
fit(Formula, DataFrame) - Static method in class smile.classification.AdaBoost
Fits a AdaBoost model.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.AdaBoost
Fits a AdaBoost model.
fit(Formula, DataFrame, int, int, int, int) - Static method in class smile.classification.AdaBoost
Fits a AdaBoost model.
fit(int[]) - Static method in class smile.classification.ClassLabels
Learns the class label mapping from samples.
fit(BaseVector) - Static method in class smile.classification.ClassLabels
Learns the class label mapping from samples.
fit(Formula, DataFrame) - Static method in class smile.classification.DecisionTree
Learns a classification tree.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.DecisionTree
Learns a classification tree.
fit(Formula, DataFrame, SplitRule, int, int, int) - Static method in class smile.classification.DecisionTree
Learns a classification tree.
fit(Formula, DataFrame) - Static method in class smile.classification.FLD
Learn Fisher's linear discriminant.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.FLD
Learn Fisher's linear discriminant.
fit(double[][], int[]) - Static method in class smile.classification.FLD
Learn Fisher's linear discriminant.
fit(double[][], int[], int, double) - Static method in class smile.classification.FLD
Learn Fisher's linear discriminant.
fit(Formula, DataFrame) - Static method in class smile.classification.GradientTreeBoost
Fits a gradient tree boosting for classification.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.GradientTreeBoost
Fits a gradient tree boosting for classification.
fit(Formula, DataFrame, int, int, int, int, double, double) - Static method in class smile.classification.GradientTreeBoost
Fits a gradient tree boosting for classification.
fit(double[], int[]) - Static method in class smile.classification.IsotonicRegressionScaling
Trains the Isotonic Regression scaling.
fit(T[], int[], Distance<T>) - Static method in class smile.classification.KNN
Learn the 1-NN classifier.
fit(T[], int[], int, Distance<T>) - Static method in class smile.classification.KNN
Learn the K-NN classifier.
fit(double[][], int[]) - Static method in class smile.classification.KNN
Learn the 1-NN classifier.
fit(double[][], int[], int) - Static method in class smile.classification.KNN
Learn the K-NN classifier.
fit(Formula, DataFrame) - Static method in class smile.classification.LDA
Learns linear discriminant analysis.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.LDA
Learns linear discriminant analysis.
fit(double[][], int[]) - Static method in class smile.classification.LDA
Learns linear discriminant analysis.
fit(double[][], int[], Properties) - Static method in class smile.classification.LDA
Learns linear discriminant analysis.
fit(double[][], int[], double[], double) - Static method in class smile.classification.LDA
Learns linear discriminant analysis.
fit(Formula, DataFrame) - Static method in class smile.classification.LogisticRegression
Fits logistic regression.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.LogisticRegression
Fits logistic regression.
fit(double[][], int[]) - Static method in class smile.classification.LogisticRegression
Fits logistic regression.
fit(double[][], int[], Properties) - Static method in class smile.classification.LogisticRegression
Fits logistic regression.
fit(double[][], int[], double, double, int) - Static method in class smile.classification.LogisticRegression
Fits logistic regression.
fit(int, int[][], int[]) - Static method in class smile.classification.Maxent
Learn maximum entropy classifier.
fit(int, int[][], int[], Properties) - Static method in class smile.classification.Maxent
Learn maximum entropy classifier.
fit(int, int[][], int[], double, double, int) - Static method in class smile.classification.Maxent
Learn maximum entropy 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[], 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[], BiFunction<T[], int[], Classifier<T>>) - Static method in class smile.classification.OneVersusRest
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(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(Classifier<T>, T[], int[]) - Static method in class smile.classification.PlattScaling
Fits Platt Scaling to estimate posteriori probabilities.
fit(Formula, DataFrame) - Static method in class smile.classification.QDA
Learns quadratic discriminant analysis.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.QDA
Learns quadratic discriminant analysis.
fit(double[][], int[]) - Static method in class smile.classification.QDA
Learn quadratic discriminant analysis.
fit(double[][], int[], Properties) - Static method in class smile.classification.QDA
Learns quadratic discriminant analysis.
fit(double[][], int[], double[], double) - Static method in class smile.classification.QDA
Learn quadratic discriminant analysis.
fit(Formula, DataFrame) - Static method in class smile.classification.RandomForest
Fits a random forest for classification.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.RandomForest
Fits a random forest for classification.
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(T[], int[], RBF<T>[]) - Static method in class smile.classification.RBFNetwork
Fits a RBF network.
fit(T[], int[], RBF<T>[], boolean) - Static method in class smile.classification.RBFNetwork
Fits a RBF network.
fit(Formula, DataFrame) - Static method in class smile.classification.RDA
Learns regularized discriminant analysis.
fit(Formula, DataFrame, Properties) - Static method in class smile.classification.RDA
Learns regularized discriminant analysis.
fit(double[][], int[], Properties) - Static method in class smile.classification.RDA
Learns regularized discriminant analysis.
fit(double[][], int[], double) - Static method in class smile.classification.RDA
Learn regularized discriminant analysis.
fit(double[][], int[], double, double[], double) - Static method in class smile.classification.RDA
Learn regularized discriminant analysis.
fit(SparseDataset, int[]) - Static method in class smile.classification.SparseLogisticRegression
Fits logistic regression.
fit(SparseDataset, int[], Properties) - Static method in class smile.classification.SparseLogisticRegression
Fits logistic regression.
fit(SparseDataset, int[], double, double, int) - Static method in class smile.classification.SparseLogisticRegression
Fits logistic regression.
fit(double[][], int[], double, double) - Static method in class smile.classification.SVM
Fits a binary-class linear SVM.
fit(int[][], int[], int, double, double) - Static method in class smile.classification.SVM
Fits a binary-class linear SVM of binary sparse data.
fit(SparseArray[], int[], int, double, double) - Static method in class smile.classification.SVM
Fits a binary-class linear SVM.
fit(T[], int[], MercerKernel<T>, double, double) - Static method in class smile.classification.SVM
Fits a binary-class SVM.
fit(T[], Distance<T>, int) - Static method in class smile.clustering.CLARANS
Clustering data into k clusters.
fit(T[], Distance<T>, int, int) - Static method in class smile.clustering.CLARANS
Constructor.
fit(double[][], int, double) - Static method in class smile.clustering.DBSCAN
Clustering the data with KD-tree.
fit(T[], Distance<T>, int, double) - Static method in class smile.clustering.DBSCAN
Clustering the data.
fit(T[], RNNSearch<T, T>, int, double) - Static method in class smile.clustering.DBSCAN
Clustering the data.
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.clustering.DeterministicAnnealing
Clustering data into k clusters.
fit(double[][], int, double, int, double, double) - 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, int, double) - Static method in class smile.clustering.GMeans
Clustering data with the number of clusters determined by G-Means algorithm automatically.
fit(Linkage) - Static method in class smile.clustering.HierarchicalClustering
Fits the Agglomerative Hierarchical Clustering with given linkage method, which includes proximity matrix.
fit(double[][], int) - 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.KMeans
Partitions data into k clusters up to 100 iterations.
fit(BBDTree, double[][], int, int, double) - Static method in class smile.clustering.KMeans
Partitions data into k clusters.
fit(int[][], int) - Static method in class smile.clustering.KModes
Fits k-modes clustering.
fit(int[][], int, int) - Static method in class smile.clustering.KModes
Fits k-modes clustering.
fit(T[], Distance<T>, int, double) - Static method in class smile.clustering.MEC
Clustering the data.
fit(T[], RNNSearch<T, T>, int, double, int[], double) - Static method in class smile.clustering.MEC
Clustering the data.
fit(SparseArray[], int) - Static method in class smile.clustering.SIB
Clustering data into k clusters up to 100 iterations.
fit(SparseArray[], int, int) - Static method in class smile.clustering.SIB
Clustering data into k clusters.
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(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, int, double) - Static method in class smile.clustering.SpectralClustering
Spectral clustering with Nystrom approximation.
fit(double[][], int, int, double, int, double) - Static method in class smile.clustering.SpectralClustering
Spectral clustering with Nystrom approximation.
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, int, double) - Static method in class smile.clustering.XMeans
Clustering data with the number of clusters determined by X-Means algorithm automatically.
fit(DataFrame) - Static method in class smile.feature.MaxAbsScaler
Learns transformation parameters from a dataset.
fit(double[][]) - Static method in class smile.feature.MaxAbsScaler
Learns transformation parameters from a dataset.
fit(DataFrame) - Static method in class smile.feature.RobustStandardizer
Learns transformation parameters from a dataset.
fit(double[][]) - Static method in class smile.feature.RobustStandardizer
Learns transformation parameters from a dataset.
fit(DataFrame) - Static method in class smile.feature.Scaler
Learns transformation parameters from a dataset.
fit(double[][]) - Static method in class smile.feature.Scaler
Learns transformation parameters from a dataset.
fit(DataFrame) - Static method in class smile.feature.Standardizer
Learns transformation parameters from a dataset.
fit(double[][]) - Static method in class smile.feature.Standardizer
Learns transformation parameters from a dataset.
fit(DataFrame) - Static method in class smile.feature.WinsorScaler
Learns transformation parameters from a dataset with 5% lower limit and 95% upper limit.
fit(DataFrame, double, double) - Static method in class smile.feature.WinsorScaler
Learns transformation parameters from a dataset.
fit(double[][]) - Static method in class smile.feature.WinsorScaler
Learns transformation parameters from a dataset.
fit(double[][], double, double) - Static method in class smile.feature.WinsorScaler
Learns transformation parameters from a dataset.
fit(T) - Method in interface smile.gap.FitnessMeasure
Returns the non-negative fitness value of a chromosome.
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, Properties) - 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(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(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(String[][], PennTreebankPOS[][]) - Static method in class smile.nlp.pos.HMMPOSTagger
Fits an HMM POS tagger by maximum likelihood estimation.
fit(double[][], int) - Static method in class smile.projection.ICA
Fits independent component analysis.
fit(double[][], int, Properties) - Static method in class smile.projection.ICA
Fits independent component analysis.
fit(double[][], int, DifferentiableFunction, double, int) - Static method in class smile.projection.ICA
Fits independent component analysis.
fit(T[], MercerKernel<T>, int) - Static method in class smile.projection.KPCA
Fits kernel principal component analysis.
fit(T[], MercerKernel<T>, int, double) - Static method in class smile.projection.KPCA
Fits kernel principal component analysis.
fit(double[][]) - Static method in class smile.projection.PCA
Fits principal component analysis with covariance matrix.
fit(double[][], int) - Static method in class smile.projection.ProbabilisticPCA
Fits probabilistic principal component analysis.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.ElasticNet
Fit an Elastic Net model.
fit(Formula, DataFrame, double, double) - Static method in class smile.regression.ElasticNet
Fit an Elastic Net model.
fit(Formula, DataFrame, double, double, double, int) - Static method in class smile.regression.ElasticNet
Fit an Elastic Net model.
fit(T[], double[], MercerKernel<T>, double) - 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(Formula, DataFrame) - Static method in class smile.regression.GradientTreeBoost
Fits a gradient tree boosting for regression.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.GradientTreeBoost
Fits a gradient tree boosting for regression.
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) - Static method in class smile.regression.LASSO
Fits a L1-regularized least squares model.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.LASSO
Fits a L1-regularized least squares model.
fit(Formula, DataFrame, double) - Static method in class smile.regression.LASSO
Fits a L1-regularized least squares model.
fit(Formula, DataFrame, double, double, int) - 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, Properties) - Static method in class smile.regression.OLS
Fits an ordinary least squares model.
fit(Formula, DataFrame, String, boolean, boolean) - Static method in class smile.regression.OLS
Fits an ordinary least squares model.
fit(Formula, DataFrame) - Static method in class smile.regression.RandomForest
Learns a random forest for regression.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.RandomForest
Learns a random forest for regression.
fit(Formula, DataFrame, int, int, int, int, int, double) - Static method in class smile.regression.RandomForest
Learns a random forest for regression.
fit(Formula, DataFrame, int, int, int, int, int, double, LongStream) - Static method in class smile.regression.RandomForest
Learns a random forest for regression.
fit(T[], double[], RBF<T>[]) - Static method in class smile.regression.RBFNetwork
Fits a RBF network.
fit(T[], double[], RBF<T>[], boolean) - Static method in class smile.regression.RBFNetwork
Fits a RBF network.
fit(Formula, DataFrame) - Static method in class smile.regression.RegressionTree
Learns a regression tree.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.RegressionTree
Learns a regression tree.
fit(Formula, DataFrame, int, int, int) - Static method in class smile.regression.RegressionTree
Learns a regression tree.
fit(Formula, DataFrame) - Static method in class smile.regression.RidgeRegression
Fits a ridge regression model.
fit(Formula, DataFrame, Properties) - Static method in class smile.regression.RidgeRegression
Fits a ridge regression 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(double[][], double[], double, double, double) - Static method in class smile.regression.SVR
Fits a linear epsilon-SVR.
fit(int[][], double[], int, double, double, double) - Static method in class smile.regression.SVR
Fits a linear epsilon-SVR of binary sparse data.
fit(SparseArray[], double[], int, double, double, double) - Static method in class smile.regression.SVR
Fits a linear epsilon-SVR of sparse data.
fit(T[], double[], MercerKernel<T>, double, double, double) - Static method in class smile.regression.SVR
Fits a epsilon-SVR.
fit(Tuple[][], int[][]) - 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(Tuple[][], int[][], int, int, int, int, double) - Static method in class smile.sequence.CRF
Fits a CRF model.
fit(T[][], int[][], Function<T, Tuple>) - Static method in class smile.sequence.CRFLabeler
Fits a CRF model.
fit(T[][], int[][], Function<T, Tuple>, Properties) - 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(int[][], int[][]) - 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.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(int[]) - Static method in class smile.stat.distribution.BernoulliDistribution
Estimates the distribution parameters by MLE.
fit(double[]) - Static method in class smile.stat.distribution.BetaDistribution
Estimates the distribution parameters by the moment method.
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[]) - Static method in class smile.stat.distribution.EmpiricalDistribution
Estimates the distribution.
fit(int[], IntSet) - Static method in class smile.stat.distribution.EmpiricalDistribution
Estimates the distribution.
fit(double[]) - Static method in class smile.stat.distribution.ExponentialDistribution
Estimates the distribution parameters by MLE.
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(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(int, 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.GaussianMixture
Fits the Gaussian mixture model with the EM algorithm.
fit(int[]) - Static method in class smile.stat.distribution.GeometricDistribution
Estimates the distribution parameters by MLE.
fit(double[]) - Static method in class smile.stat.distribution.LogNormalDistribution
Estimates the distribution parameters by MLE.
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[][]) - Static method in class smile.stat.distribution.MultivariateGaussianDistribution
Estimates the mean and diagonal covariance by MLE.
fit(double[][], boolean) - Static method in class smile.stat.distribution.MultivariateGaussianDistribution
Estimates the mean and covariance by MLE.
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(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.MultivariateGaussianMixture
Fits the Gaussian mixture model with the EM algorithm.
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(double[], int) - Static method in class smile.timeseries.AR
Fits an autoregressive model with Yule-Walker procedure.
fit(double[], int, int) - Static method in class smile.timeseries.ARMA
Fits an ARMA model with Hannan-Rissanen algorithm.
fitness(double[][], int[], double[][], int[], ClassificationMeasure, BiFunction<double[][], int[], Classifier<double[]>>) - Static method in class smile.feature.GAFE
Returns a classification fitness measure.
fitness(double[][], double[], double[][], double[], RegressionMeasure, BiFunction<double[][], double[], Regression<double[]>>) - Static method in class smile.feature.GAFE
Returns a regression fitness measure.
fitness(String, DataFrame, DataFrame, ClassificationMeasure, BiFunction<Formula, DataFrame, DataFrameClassifier>) - Static method in class smile.feature.GAFE
Returns a classification fitness measure.
fitness(String, DataFrame, DataFrame, RegressionMeasure, BiFunction<Formula, DataFrame, DataFrameRegression>) - Static method in class smile.feature.GAFE
Returns a regression fitness measure.
fitness() - Method in class smile.gap.BitString
 
fitness() - Method in interface smile.gap.Chromosome
Returns the fitness of chromosome.
FitnessMeasure<T extends Chromosome> - Interface in smile.gap
A measure to evaluate the fitness of chromosomes.
fittedValues() - Method in class smile.glm.GLM
Returns the fitted mean values.
fittedValues - Variable in class smile.math.LevenbergMarquardt
The fitted 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.
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_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)
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.
FloatBandMatrix - 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.
FloatBandMatrix(int, int, int, int) - Constructor for class smile.math.matrix.FloatBandMatrix
Constructor.
FloatBandMatrix(int, int, int, int, float[][]) - Constructor for class smile.math.matrix.FloatBandMatrix
Constructor.
FloatBandMatrix.Cholesky - Class in smile.math.matrix
The Cholesky decomposition of a symmetric, positive-definite matrix.
FloatBandMatrix.LU - Class in smile.math.matrix
The LU decomposition.
FloatConsumer - Interface in smile.math.matrix
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(int) - Constructor for class smile.sort.FloatHeapSelect
Constructor.
FloatHeapSelect(float[]) - Constructor for class smile.sort.FloatHeapSelect
Constructor.
FloatMatrix - Class in smile.math.matrix
 
FloatMatrix(int, int) - Constructor for class smile.math.matrix.FloatMatrix
Constructor of zero matrix.
FloatMatrix(int, int, float) - Constructor for class smile.math.matrix.FloatMatrix
Constructor.
FloatMatrix(int, int, float[][]) - Constructor for class smile.math.matrix.FloatMatrix
Constructor.
FloatMatrix(float[][]) - Constructor for class smile.math.matrix.FloatMatrix
Constructor.
FloatMatrix(float[]) - Constructor for class smile.math.matrix.FloatMatrix
Constructor of a column vector/matrix with given array as the internal storage.
FloatMatrix(float[], int, int) - Constructor for class smile.math.matrix.FloatMatrix
Constructor of a column vector/matrix with given array as the internal storage.
FloatMatrix(int, int, int, FloatBuffer) - Constructor for class smile.math.matrix.FloatMatrix
Constructor.
FloatMatrix.Cholesky - Class in smile.math.matrix
The Cholesky decomposition of a symmetric, positive-definite matrix.
FloatMatrix.EVD - Class in smile.math.matrix
Eigenvalue decomposition.
FloatMatrix.LU - Class in smile.math.matrix
The LU decomposition.
FloatMatrix.QR - Class in smile.math.matrix
The QR decomposition.
FloatMatrix.SVD - Class in smile.math.matrix
Singular Value Decomposition.
FloatObjectType - Static variable in class smile.data.type.DataTypes
Float Object data type.
FloatSparseMatrix - Class in smile.math.matrix
A sparse matrix is a matrix populated primarily with zeros.
FloatSparseMatrix(int, int, float[], int[], int[]) - Constructor for class smile.math.matrix.FloatSparseMatrix
Constructor.
FloatSparseMatrix(float[][]) - Constructor for class smile.math.matrix.FloatSparseMatrix
Constructor.
FloatSparseMatrix(float[][], float) - Constructor for class smile.math.matrix.FloatSparseMatrix
Constructor.
FloatSparseMatrix.Entry - Class in smile.math.matrix
Encapsulates an entry in a matrix for use in streaming.
FloatSymmMatrix - Class in smile.math.matrix
They symmetric matrix in packed storage.
FloatSymmMatrix(UPLO, int) - Constructor for class smile.math.matrix.FloatSymmMatrix
Constructor.
FloatSymmMatrix(UPLO, float[][]) - Constructor for class smile.math.matrix.FloatSymmMatrix
Constructor.
FloatSymmMatrix.BunchKaufman - Class in smile.math.matrix
The LU decomposition.
FloatSymmMatrix.Cholesky - Class in smile.math.matrix
The Cholesky decomposition of a symmetric, positive-definite matrix.
FloatType - Static variable in class smile.data.type.DataTypes
Float data type.
FloatType - Class in smile.data.type
Float data type.
floatVector(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
floatVector(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
floatVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
floatVector(int) - Method in class smile.data.IndexDataFrame
 
FloatVector - Interface in smile.data.vector
An immutable float vector.
floor(String) - Static method in interface smile.data.formula.Terms
Applies Math.floor.
floor(Term) - Static method in interface smile.data.formula.Terms
Applies Math.floor.
FMeasure - Class in smile.validation
The F-score (or F-measure) considers both the precision and the recall of the test to compute the score.
FMeasure() - Constructor for class smile.validation.FMeasure
Constructor of F1 score.
FMeasure(double) - Constructor for class smile.validation.FMeasure
Constructor of general F-score.
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(DoubleConsumer) - Method in class smile.math.matrix.FloatSparseMatrix
For each loop on non-zero elements.
forEachNonZero(int, int, FloatConsumer) - Method in class smile.math.matrix.FloatSparseMatrix
For each loop on non-zero elements.
forEachNonZero(DoubleConsumer) - Method in class smile.math.matrix.SparseMatrix
For each loop on non-zero elements.
forEachNonZero(int, int, 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(int) - Method in class smile.timeseries.AR
Returns l-step ahead forecast.
forecast() - Method in class smile.timeseries.ARMA
Returns 1-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(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(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.
formula - Variable in class smile.base.cart.CART
The model formula.
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 - 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.
formula() - Method in interface smile.feature.TreeSHAP
Returns the formula associated with the model.
formula - Variable in class smile.glm.GLM
The symbolic description of the model to be fitted.
formula() - Method in interface smile.regression.DataFrameRegression
Returns the formula associated with the model.
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.
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(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.
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.
Function - Interface in smile.math
An interface representing a univariate real function.

G

g(double[], double[]) - Method in interface smile.base.mlp.ActivationFunction
The gradient function.
g(Cost, double[], double[]) - Method in enum smile.base.mlp.OutputFunction
The gradient function.
g(double[], double[]) - Method in class smile.math.AbstractDifferentiableMultivariateFunction
 
g(double) - Method in interface smile.math.DifferentiableFunction
Computes the gradient/derivative at x.
g(double[], double[]) - Method in interface smile.math.DifferentiableMultivariateFunction
Computes the value and gradient at x.
g(double) - Method in class smile.projection.ica.Exp
 
g(double) - Method in class smile.projection.ica.Kurtosis
 
g(double) - Method in class smile.projection.ica.LogCosh
 
g2(double) - Method in interface smile.math.DifferentiableFunction
Compute the second-order derivative at x.
g2(double) - Method in class smile.projection.ica.Exp
 
g2(double) - Method in class smile.projection.ica.Kurtosis
 
g2(double) - Method in class smile.projection.ica.LogCosh
 
GAFE - Class in smile.feature
Genetic algorithm based feature selection.
GAFE() - Constructor for class smile.feature.GAFE
Constructor.
GAFE(Selection, int, Crossover, double, double) - Constructor for class smile.feature.GAFE
Constructor.
Gamma - Class in smile.math.special
The gamma, digamma, and incomplete gamma functions.
gamma(double) - Static method in class smile.math.special.Gamma
Gamma function.
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.
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
The Gaussian Kernel.
GaussianKernel(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 - Class in smile.regression
Gaussian Process for Regression.
GaussianProcessRegression() - Constructor for class smile.regression.GaussianProcessRegression
 
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, 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, 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, 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, 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 class smile.math.blas.openblas.OpenBLAS
 
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 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, 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, 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, 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, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, 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, 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, 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, double[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
gbtrf(Layout, int, int, int, int, DoubleBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
gbtrf(Layout, int, int, int, int, float[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, 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, 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, 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, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gbtrs(Layout, Transpose, int, int, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, 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, 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, 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, double[], int, double[], double[], double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, float[], int, float[], float[], float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
geev(Layout, EVDJob, EVDJob, int, FloatBuffer, int, FloatBuffer, FloatBuffer, FloatBuffer, int, FloatBuffer, 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, 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, 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, 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, double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gels(Layout, Transpose, int, int, int, DoubleBuffer, int, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gels(Layout, Transpose, int, int, int, float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, 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, 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, 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, double[], int, double[], int, double[], double, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, float[], int, float[], int, float[], float, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, 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, 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, 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, double[], int, double[], int, double[], double, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, float[], int, float[], int, float[], float, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, 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, 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, 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, double[], int, double[], int, int[], double, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, float[], int, float[], int, int[], float, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
gelsy(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, IntBuffer, float, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, 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, 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, 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, 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 class smile.math.blas.openblas.OpenBLAS
 
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 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, DoubleBuffer, int, DoubleBuffer, int, double, DoubleBuffer, 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 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 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 class smile.math.blas.openblas.OpenBLAS
 
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 class smile.math.blas.openblas.OpenBLAS
 
GeneticAlgorithm<T extends Chromosome> - 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, 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, 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, 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, double[], int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
geqrf(Layout, int, int, DoubleBuffer, int, DoubleBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
geqrf(Layout, int, int, float[], int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
geqrf(Layout, int, int, FloatBuffer, int, FloatBuffer) - 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, DoubleBuffer, int, DoubleBuffer, int, DoubleBuffer, 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 interface smile.math.blas.BLAS
Performs the rank-1 update operation.
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, 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 class smile.math.blas.openblas.OpenBLAS
 
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 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, 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, 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, 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, double[], int, double[], double[], int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, float[], int, float[], float[], int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesdd(Layout, SVDJob, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int, FloatBuffer, 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, DoubleBuffer, int, IntBuffer, DoubleBuffer, 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 interface smile.math.blas.LAPACK
Solves a real system of linear equations.
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, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesv(Layout, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesv(Layout, int, int, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesv(Layout, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, 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, 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, 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, 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, double[], int, double[], double[], int, double[], int, double[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, float[], int, float[], float[], int, float[], int, float[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
gesvd(Layout, SVDJob, SVDJob, int, int, FloatBuffer, int, FloatBuffer, FloatBuffer, int, FloatBuffer, int, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, String) - Method in interface smile.data.DataFrame
Returns the cell at (i, j).
get(int) - Method in interface smile.data.Dataset
Returns the element at the specified position in this dataset.
get(int, int) - Method in class smile.data.IndexDataFrame
 
get(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) - Method in interface smile.data.Tuple
Returns the value at position i.
get(String) - Method in interface smile.data.Tuple
Returns the value by field name.
get(int) - Method in interface smile.data.vector.BaseVector
Returns the value at position i, which may be null.
get(int...) - Method in interface smile.data.vector.BaseVector
Returns a new vector with selected entries.
get(String) - Method in class smile.hash.PerfectHash
Returns the index of a string.
get(String) - Method in class smile.hash.PerfectMap
Returns the value associated with the key.
get(int) - Method in class smile.math.Complex.Array
Returns the i-th element.
get(int, int) - Method in class smile.math.matrix.BandMatrix
 
get(int, int) - Method in class smile.math.matrix.DMatrix
Returns A[i, j].
get(int, int) - Method in class smile.math.matrix.FloatBandMatrix
 
get(int, int) - Method in class smile.math.matrix.FloatMatrix
 
get(int) - Method in class smile.math.matrix.FloatSparseMatrix
Returns the element at the storage index.
get(int, int) - Method in class smile.math.matrix.FloatSparseMatrix
 
get(int, int) - Method in class smile.math.matrix.FloatSymmMatrix
 
get(int, int) - Method in class smile.math.matrix.Matrix
 
get(int, int) - Method in class smile.math.matrix.SMatrix
Returns A[i, j].
get(int) - Method in class smile.math.matrix.SparseMatrix
Returns the element at the storage index.
get(int, int) - Method in class smile.math.matrix.SparseMatrix
 
get(int, int) - Method in class smile.math.matrix.SymmMatrix
 
get(int) - Method in class smile.neighbor.lsh.Hash
Returns the bucket entry for the given hash value.
get(double[]) - Method in class smile.neighbor.lsh.Hash
Returns the bucket entry for the given point.
get(String) - Method in class smile.nlp.embedding.Word2Vec
Returns the vector embedding of a word.
get(String) - Static method in class smile.nlp.pos.EnglishPOSLexicon
Returns 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 associated value of a given key.
get(K) - Method in class smile.nlp.Trie
Returns the node of a given key.
get(int, int) - Method in interface smile.plot.swing.Hexmap.Tooltip
Gets the tooltip of cell at (i, j).
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, int) - Method in class smile.util.Array2D
Returns A(i, j).
get(int) - Method in class smile.util.DoubleArrayList
Returns the value at the specified position in this list.
get(int, int) - Method in class smile.util.IntArray2D
Returns A(i, j).
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.
getAbbreviation(String) - Method in interface smile.nlp.dictionary.Abbreviations
Returns the abbreviation for a word.
getAlpha() - Method in class smile.stat.distribution.BetaDistribution
Returns the shape parameter alpha.
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, 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(int) - Method in interface smile.data.Tuple
Returns the value at position i 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.
getAverageDocumentSize() - Method in interface smile.nlp.Corpus
Returns the average size of documents in the corpus.
getAverageDocumentSize() - Method in class smile.nlp.SimpleCorpus
 
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.
getBeta() - Method in class smile.stat.distribution.BetaDistribution
Returns the shape parameter beta.
getBigramFrequency(Bigram) - Method in interface smile.nlp.Corpus
Returns the total frequency of the bigram in the corpus.
getBigramFrequency(Bigram) - Method in class smile.nlp.SimpleCorpus
 
getBigrams() - Method in interface smile.nlp.Corpus
Returns an iterator over the bigrams in the corpus.
getBigrams() - Method in class smile.nlp.SimpleCorpus
 
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(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive boolean.
getBoolean(String) - Method in interface smile.data.Tuple
Returns the field value as a primitive boolean.
getBoolean(int) - Method in interface smile.data.vector.BooleanVector
Returns the value at position i.
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(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive byte.
getByte(String) - Method in interface smile.data.Tuple
Returns the field value 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.Vector
 
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
 
getCenter() - Method in class smile.projection.PCA
Returns the center of data.
getCenter() - Method in class smile.projection.ProbabilisticPCA
Returns the center of data.
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(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive byte.
getChar(String) - Method in interface smile.data.Tuple
Returns the field value as a primitive byte.
getChar(int) - Method in interface smile.data.vector.CharVector
Returns the value at position i.
getChild(K[], int) - Method in class smile.nlp.Trie.Node
 
getChild(K) - Method in class smile.nlp.Trie.Node
 
getChildren() - Method in class smile.taxonomy.Concept
Get all children concepts.
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 a concept node which synset contains the keyword.
getConcepts() - Method in class smile.taxonomy.Taxonomy
Returns all named concepts from this taxonomy
getCoordinates() - Method in class smile.projection.KPCA
Returns the nonlinear principal component scores, i.e., the representation of learning data in the nonlinear principal component space.
getCoordinateSpace() - Method in class smile.plot.swing.Base
Returns the coordinates.
getCumulativeVarianceProportion() - Method in class smile.projection.PCA
Returns the cumulative proportion of variance contained in principal components, ordered from largest to smallest.
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(int) - Method in interface smile.data.Tuple
Returns the value at position i 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, 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(int) - Method in interface smile.data.Tuple
Returns the value at position i of date type 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, 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(int) - Method in interface smile.data.Tuple
Returns the value at position i 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, 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(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive double.
getDouble(String) - Method in interface smile.data.Tuple
Returns the field value 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.Vector
 
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(int) - Method in class smile.graph.AdjacencyList
 
getEdges(int, int) - Method in class smile.graph.AdjacencyList
 
getEdges() - Method in class smile.graph.AdjacencyMatrix
 
getEdges(int) - Method in class smile.graph.AdjacencyMatrix
 
getEdges(int, int) - Method in class smile.graph.AdjacencyMatrix
 
getEdges() - Method in interface smile.graph.Graph
Returns a set of the edges contained in this graph.
getEdges(int) - Method in interface smile.graph.Graph
Returns a set of all edges from the specified vertex.
getEdges(int, int) - Method in interface smile.graph.Graph
Returns a set of all 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.
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(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive float.
getFloat(String) - Method in interface smile.data.Tuple
Returns the field value 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.Vector
 
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 for a given abbreviation.
getGraphics() - Method in class smile.plot.swing.Graphics
Returns the Java2D graphics object.
getHeight() - Method in class smile.clustering.HierarchicalClustering
Returns a set of n-1 non-decreasing real values, which are the clustering height, i.e., the value of the criterion associated with the clustering method for the particular agglomeration.
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
 
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, 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(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive int.
getInt(String) - Method in interface smile.data.Tuple
Returns the field value 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.Vector
 
getKey() - Method in class smile.nlp.Trie.Node
 
getKeywords() - Method in class smile.taxonomy.Concept
Returns the concept synonym set.
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.
getLearningRate() - Method in class smile.projection.GHA
Returns the learning rate.
getLoadings() - Method in class smile.projection.PCA
Returns the variable loading matrix, ordered from largest to smallest by corresponding eigenvalues.
getLoadings() - Method in class smile.projection.ProbabilisticPCA
Returns the variable loading matrix, ordered from largest to smallest by corresponding eigenvalues.
getLocalSearchSteps() - Method in class smile.gap.GeneticAlgorithm
Gets the number of iterations of local search for Lamarckian algorithm.
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(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive long.
getLong(String) - Method in interface smile.data.Tuple
Returns the field value 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.Vector
 
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.
getNoiseVariance() - Method in class smile.projection.ProbabilisticPCA
Returns the variance of noise.
getNumberFormat() - Method in class smile.swing.table.NumberCellRenderer
Returns the number format used for rendering.
getNumBigrams() - Method in interface smile.nlp.Corpus
Returns the number of bigrams in the corpus.
getNumBigrams() - Method in class smile.nlp.SimpleCorpus
 
getNumDocuments() - Method in interface smile.nlp.Corpus
Returns the number of documents in the corpus.
getNumDocuments() - Method in class smile.nlp.SimpleCorpus
 
getNumTerms() - Method in interface smile.nlp.Corpus
Returns the number of unique terms in the corpus.
getNumTerms() - Method in class smile.nlp.SimpleCorpus
 
getNumVertices() - Method in class smile.graph.AdjacencyList
 
getNumVertices() - Method in class smile.graph.AdjacencyMatrix
 
getNumVertices() - Method in interface smile.graph.Graph
Returns the number vertices.
getObjectClass() - Method in class smile.data.type.ObjectType
Returns the class of objects.
getOmega() - Method in class smile.math.kernel.PearsonKernel
Get the omega parameter.
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 the given node.
getPathToRoot() - Method in class smile.taxonomy.Concept
Returns the path from the given 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() - Method in class smile.projection.GHA
Returns the projection matrix.
getProjection() - Method in class smile.projection.KPCA
Returns the projection matrix.
getProjection() - Method in interface smile.projection.LinearProjection
Returns the projection matrix.
getProjection() - Method in class smile.projection.PCA
 
getProjection() - Method in class smile.projection.ProbabilisticPCA
Returns the projection matrix.
getProjection() - Method in class smile.projection.RandomProjection
 
getPropertyChangeListeners() - Method in class smile.plot.swing.Canvas
Returns an array of all the listeners that were added to the PropertyChangeSupport object with addPropertyChangeListener().
getReadableImageFilter() - Static method in class smile.swing.FileChooser.SimpleFileFilter
Returns the filter for readable images.
getRealRow(int) - Method in class smile.swing.table.PageTableModel
Returns the row number of data given the row number of current page.
getRealRowCount() - Method in class smile.swing.table.PageTableModel
The sub class should implement this method to return the real number of rows in the model.
getrf(Layout, int, int, double[], int, int[]) - Method in interface smile.math.blas.LAPACK
Computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges.
getrf(Layout, int, int, 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, 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, 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, DoubleBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf(Layout, int, int, double[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf(Layout, int, int, float[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf(Layout, int, int, FloatBuffer, int, IntBuffer) - 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, 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, 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, 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, double[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf2(Layout, int, int, DoubleBuffer, int, IntBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrf2(Layout, int, int, float[], int, int[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, DoubleBuffer, int, IntBuffer, DoubleBuffer, 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 interface smile.math.blas.LAPACK
Solves a system of linear equations
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, double[], int, int[], double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrs(Layout, Transpose, int, int, DoubleBuffer, int, IntBuffer, DoubleBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrs(Layout, Transpose, int, int, float[], int, int[], float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
getrs(Layout, Transpose, int, int, FloatBuffer, int, IntBuffer, FloatBuffer, int) - Method in class smile.math.blas.openblas.OpenBLAS
 
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(int) - Method in interface smile.data.Tuple
Returns the value at position i 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, 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(int) - Method in interface smile.data.Tuple
Returns the value at position i as a primitive short.
getShort(String) - Method in interface smile.data.Tuple
Returns the field value 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.Vector
 
getSigma() - Method in class smile.math.kernel.PearsonKernel
Get the sigma parameter.
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, 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(int) - Method in interface smile.data.Tuple
Returns the value at position i 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, 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(int) - Method in interface smile.data.Tuple
Returns the value at position i 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.
getTermFrequency(String) - Method in interface smile.nlp.Corpus
Returns the total frequency of the term in the corpus.
getTermFrequency(String) - Method in class smile.nlp.SimpleCorpus
 
getTerms() - Method in interface smile.nlp.Corpus
Returns an iterator over the terms in the corpus.
getTerms() - Method in class smile.nlp.SimpleCorpus
 
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, 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(int) - Method in interface smile.data.Tuple
Returns the value at position i of date type as java.time.LocalTime.
getTime(String) - Method in interface smile.data.Tuple
Returns the field value of date type as java.time.LocalTime.
getTitle() - Method in class smile.plot.swing.Canvas
Returns the main title of canvas.
getTitleColor() - Method in class smile.plot.swing.Canvas
Returns the color for title.
getTitleFont() - Method in class smile.plot.swing.Canvas
Returns the font for title.
getToolbar() - Method in class smile.plot.swing.PlotPanel
Returns a tool bar to control the plot.
getToolbar() - Method in class smile.swing.table.PageTableModel
Returns a tool bar to control the plot.
getTree() - Method in class smile.clustering.HierarchicalClustering
Returns an n-1 by 2 matrix of which row i describes the merging of clusters at step i of the clustering.
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(String) - Static method in enum smile.nlp.pos.PennTreebankPOS
Returns an enum value from a string.
getValue() - Method in class smile.nlp.Trie.Node
 
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.
getVariance() - Method in class smile.projection.PCA
Returns the principal component variances, ordered from largest to smallest, which are the eigenvalues of the covariance or correlation matrix of learning data.
getVarianceProportion() - Method in class smile.projection.PCA
Returns the proportion of variance contained in each principal component, ordered from largest to smallest.
getVariances() - Method in class smile.projection.KPCA
Returns the eigenvalues of kernel principal components, ordered from largest to smallest.
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, 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, 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, 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, double[], int, double[], int, double[], double[], double[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, float[], int, float[], int, float[], float[], float[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, 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, 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, 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, double[], int, double[], int, double[], double[], double[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
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, float[], int, float[], int, float[], float[], float[]) - Method in class smile.math.blas.openblas.OpenBLAS
 
gglse(Layout, int, int, int, FloatBuffer, int, FloatBuffer, int, FloatBuffer, FloatBuffer, FloatBuffer) - Method in class smile.math.blas.openblas.OpenBLAS
 
GHA - Class in smile.projection
Generalized Hebbian Algorithm.
GHA(int, int, double) - Constructor for class smile.projection.GHA
Constructor.
GHA(double[][], double) - Constructor for class smile.projection.GHA
Constructor.
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
 
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.
gradient() - Method in class smile.base.mlp.Layer
Returns the output gradient vector.
GradientTreeBoost - Class in smile.classification
Gradient boosting for classification.
GradientTreeBoost(Formula, RegressionTree[], double, double, double[]) - Constructor for class smile.classification.GradientTreeBoost
Constructor of binary class.
GradientTreeBoost(Formula, RegressionTree[], double, double, double[], IntSet) - Constructor for class smile.classification.GradientTreeBoost
Constructor of binary class.
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 - Class in smile.regression
Gradient boosting for regression.
GradientTreeBoost(Formula, RegressionTree[], double, double, double[]) - Constructor for class smile.regression.GradientTreeBoost
Constructor.
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 - 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.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 - Class in smile.plot.swing
A 2D grid plot.
Grid(double[][][], Color) - Constructor for class smile.plot.swing.Grid
Constructor.
grid() - Method in class smile.validation.Hyperparameters
Generates a stream of hyperparameters for grid search.
GroupKFold - Class in smile.validation
GroupKfold is a cross validation technique that splits the data by respecting additional information about groups.
GroupKFold(int, int, int[]) - Constructor for class smile.validation.GroupKFold
Constructor.
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.

H

H - Variable in class smile.neighbor.LSH
The size of hash table.
H - Variable in class smile.neighbor.lsh.NeighborHashValueModel
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.
harwell(Path) - Static method in class smile.math.matrix.FloatSparseMatrix
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(T) - Method in interface smile.hash.SimHash
 
Hash - Class in smile.neighbor.lsh
The hash function for Euclidean spaces.
hash - Variable in class smile.neighbor.LSH
Hash functions.
Hash(int, int, double, int) - Constructor for class smile.neighbor.lsh.Hash
Constructor.
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.
hash128(ByteBuffer, int, int, long, long[]) - Static method in class smile.hash.MurmurHash3
128-bit MurmurHash3 for x64.
hash32(ByteBuffer, int, int, int) - Static method in class smile.hash.MurmurHash2
32-bit MurmurHash.
hash32(byte[], int, int, int) - Static method in class smile.hash.MurmurHash3
32-bit MurmurHash3.
hash64(ByteBuffer, int, int, long) - Static method in class smile.hash.MurmurHash2
64-bit MurmurHash.
hashCode() - Method in class smile.association.AssociationRule
 
hashCode() - Method in class smile.association.ItemSet
 
hashCode() - Method in class smile.math.Complex
 
hashCode() - Method in class smile.nlp.Bigram
 
hashCode() - Method in class smile.nlp.NGram
 
hashCode() - Method in class smile.nlp.SimpleText
 
hashCode() - Method in class smile.util.IntPair
 
HashValueParzenModel - Class in smile.neighbor.lsh
Hash value Parzen model for multi-probe hash.
HashValueParzenModel(MultiProbeHash, MultiProbeSample[], double) - Constructor for class smile.neighbor.lsh.HashValueParzenModel
Constructor.
hasNull() - Method in interface smile.data.Tuple
Returns true if the tuple has null/missing values.
Headless - Class in smile.plot.swing
Aids in creating swing components in a "headless" environment.
Headless(JComponent, int, int) - Constructor for class smile.plot.swing.Headless
 
heapify() - Method in class smile.sort.HeapSelect
In case of avoiding creating new objects frequently, one may check and update the peek object directly and call this method to sort the internal array in heap order.
HeapSelect<T extends java.lang.Comparable<? super T>> - Class in smile.sort
This class tracks the smallest values seen thus far in a stream of values.
HeapSelect(int) - Constructor for class smile.sort.HeapSelect
Constructor.
HeapSelect(T[]) - Constructor for class smile.sort.HeapSelect
Constructor.
HeapSort - Interface in smile.sort
Heapsort is a comparison-based sorting algorithm, and is part of the selection sort family.
heat(int) - Static method in interface smile.plot.swing.Palette
Generate heat color palette.
heat(int, float) - Static method in interface smile.plot.swing.Palette
Generate heat color palette.
Heatmap - Class in smile.plot.swing
A heat map is a graphical representation of data where the values taken by a variable in a two-dimensional map are represented as colors.
Heatmap(String[], String[], double[][], Color[]) - Constructor for class smile.plot.swing.Heatmap
Constructor.
Heatmap(double[], double[], double[][], Color[]) - Constructor for class smile.plot.swing.Heatmap
Constructor.
HellingerKernel - Class in smile.math.kernel
The Hellinger Mercer Kernel.
HellingerKernel() - Constructor for class smile.math.kernel.HellingerKernel
Constructor.
Hexmap - Class in smile.plot.swing
Hexmap is a variant of heat map by replacing rectangle cells with hexagon cells.
Hexmap(double[][], Color[], Hexmap.Tooltip) - Constructor for class smile.plot.swing.Hexmap
Constructor.
Hexmap.Tooltip - Interface in smile.plot.swing
The lambda interface to retrieve the tooltip of cell.
HHMM - Static variable in class smile.swing.table.DateCellEditor
 
HHMM - Static variable in class smile.swing.table.DateCellRenderer
 
HHMMSS - Static variable in class smile.swing.table.DateCellEditor
 
HHMMSS - Static variable in class smile.swing.table.DateCellRenderer
 
HiddenLayer - Class in smile.base.mlp
A hidden layer in the neural network.
HiddenLayer(int, int, ActivationFunction) - Constructor for class smile.base.mlp.HiddenLayer
Constructor.
HierarchicalClustering - Class in smile.clustering
Agglomerative Hierarchical Clustering.
HierarchicalClustering(int[][], double[]) - Constructor for class smile.clustering.HierarchicalClustering
Constructor.
Histogram - Interface in smile.math
Histogram utilities.
Histogram - Class in smile.plot.swing
A histogram is a graphical display of tabulated frequencies, shown as bars.
Histogram() - Constructor for class smile.plot.swing.Histogram
 
Histogram3D - Class in smile.plot.swing
A histogram is a graphical display of tabulated frequencies, shown as bars.
Histogram3D(double[][], int, int, boolean, Color[]) - Constructor for class smile.plot.swing.Histogram3D
Constructor.
HMM - Class in smile.sequence
First-order Hidden Markov Model.
HMM(double[], Matrix, Matrix) - Constructor for class smile.sequence.HMM
Constructor.
HMMLabeler<T> - Class in smile.sequence
First-order Hidden Markov Model sequence labeler.
HMMLabeler(HMM, ToIntFunction<T>) - Constructor for class smile.sequence.HMMLabeler
Constructor.
HMMPOSTagger - Class in smile.nlp.pos
Part-of-speech tagging with hidden Markov model.
HMMPOSTagger() - Constructor for class smile.nlp.pos.HMMPOSTagger
Constructor.
home - Static variable in interface smile.util.Paths
Smile home directory.
hsv(float, float, float, float) - Static method in interface smile.plot.swing.Palette
Generate a color based on HSV model.
huber(double) - Static method in interface smile.base.cart.Loss
Huber loss function for M-regression, which attempts resistance to long-tailed error distributions and outliers while maintaining high efficiency for normally distributed errors.
HyperbolicTangentKernel - Class in smile.math.kernel
The hyperbolic tangent kernel.
HyperbolicTangentKernel() - Constructor for class smile.math.kernel.HyperbolicTangentKernel
Constructor.
HyperbolicTangentKernel(double, double) - Constructor for class smile.math.kernel.HyperbolicTangentKernel
Constructor.
HyperGeometricDistribution - Class in smile.stat.distribution
The hypergeometric distribution is a discrete probability distribution that describes the number of successes in a sequence of n draws from a finite population without replacement, just as the binomial distribution describes the number of successes for draws with replacement.
HyperGeometricDistribution(int, int, int) - Constructor for class smile.stat.distribution.HyperGeometricDistribution
Constructor.
Hyperparameters - Class in smile.validation
Hyperparameter tuning.
Hyperparameters() - Constructor for class smile.validation.Hyperparameters
Constructor.
Hypothesis - Interface in smile.stat
Hypothesis test functions.
Hypothesis.chisq - Interface in smile.stat
Chi-square test.
Hypothesis.cor - Interface in smile.stat
Correlation test.
Hypothesis.F - Interface in smile.stat
F-test.
Hypothesis.KS - Interface in smile.stat
The Kolmogorov-Smirnov test (K-S test).
Hypothesis.t - Interface in smile.stat
t-test.

I

i - Variable in class smile.math.matrix.FloatSparseMatrix.Entry
The row index.
i - Variable in class smile.math.matrix.SparseMatrix.Entry
The row index.
i - Variable in class smile.util.IntPair
 
i - Variable in class smile.util.SparseArray.Entry
The index of entry.
iamax(int, double[], int) - Method in interface smile.math.blas.BLAS
Searches a vector for the first occurrence of the the maximum absolute value.
iamax(int, float[], int) - Method in interface smile.math.blas.BLAS
Searches a vector for the first occurrence of the the maximum absolute value.
iamax(double[]) - Method in interface smile.math.blas.BLAS
Searches a vector for the first occurrence of the the maximum absolute value.
iamax(float[]) - Method in interface smile.math.blas.BLAS
Searches a vector for the first occurrence of the the maximum absolute value.
iamax(int, double[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
iamax(int, float[], int) - Method in class smile.math.blas.openblas.OpenBLAS
 
ICA - Class in smile.projection
Independent Component Analysis (ICA) is a computational method for separating a multivariate signal into additive components.
ICA(double[][]) - Constructor for class smile.projection.ICA
Constructor.
id() - Method in class smile.data.type.ArrayType
 
id() - Method in class smile.data.type.BooleanType
 
id() - Method in class smile.data.type.ByteType
 
id() - Method in class smile.data.type.CharType
 
id() - Method in interface smile.data.type.DataType
Returns the type ID enum.
id() - Method in class smile.data.type.DateTimeType
 
id() - Method in class smile.data.type.DateType
 
id() - Method in class smile.data.type.DecimalType
 
id() - Method in class smile.data.type.DoubleType
 
id() - Method in class smile.data.type.FloatType
 
id() - Method in class smile.data.type.IntegerType
 
id() - Method in class smile.data.type.LongType
 
id() - Method in class smile.data.type.ObjectType
 
id() - Method in class smile.data.type.ShortType
 
id() - Method in class smile.data.type.StringType
 
id() - Method in class smile.data.type.StructType
 
id() - Method in class smile.data.type.TimeType
 
id - Variable in class smile.nlp.Text
The id of document in the corpus.
im - Variable in class smile.math.Complex
The imaginary part.
IMatrix<T> - Class in smile.math.matrix
An abstract interface of matrix.
IMatrix() - Constructor for class smile.math.matrix.IMatrix
 
importance - Variable in class smile.base.cart.CART
Variable importance.
importance() - Method in class smile.base.cart.CART
Returns the variable importance.
importance() - Method in class smile.classification.AdaBoost
Returns the variable importance.
importance() - Method in class smile.classification.GradientTreeBoost
Returns the variable importance.
importance() - Method in class smile.classification.RandomForest
Returns the variable importance.
importance() - Method in class smile.regression.GradientTreeBoost
Returns the variable importance.
importance() - Method in class smile.regression.RandomForest
Returns the variable importance.
impurity(LeafNode) - Method in class smile.base.cart.CART
Returns the impurity of node.
impurity(SplitRule) - Method in class smile.base.cart.DecisionNode
Returns the impurity of node.
impurity(SplitRule, int, int[]) - Static method in class smile.base.cart.DecisionNode
Returns the impurity of samples.
impurity() - Method in class smile.base.cart.RegressionNode
Returns the residual sum of squares.
impurity(LeafNode) - Method in class smile.classification.DecisionTree
 
impurity(LeafNode) - Method in class smile.regression.RegressionTree
 
impute(double[][]) - Method in class smile.imputation.AverageImputation
 
impute(double[][]) - Method in class smile.imputation.KMeansImputation
 
impute(double[][]) - Method in class smile.imputation.KNNImputation
 
impute(double[][]) - Method in class smile.imputation.LLSImputation
 
impute(double[][]) - Method in interface smile.imputation.MissingValueImputation
Impute missing values in the data.
impute(double[][]) - Method in class smile.imputation.SVDImputation
 
impute(double[][], int) - Method in class smile.imputation.SVDImputation
Impute missing values in the dataset.
imputeWithColumnAverage(double[][]) - Static method in interface smile.imputation.MissingValueImputation
Impute the missing values with column averages.
increment() - Method in class smile.util.MutableInt
Increment by one.
increment(int) - Method in class smile.util.MutableInt
Increment.
index - Variable in class smile.base.cart.CART
An index of samples to their original locations in training dataset.
index - Variable in class smile.manifold.IsoMap
The original sample index.
index - Variable in class smile.manifold.LaplacianEigenmap
The original sample index.
index - Variable in class smile.manifold.LLE
The original sample index.
index - Variable in class smile.manifold.UMAP
The original sample index.
index(int, int) - Method in class smile.math.matrix.FloatMatrix
Returns the linear index of matrix element.
index - Variable in class smile.math.matrix.FloatSparseMatrix.Entry
The index to the matrix storage.
index(int, int) - Method in class smile.math.matrix.Matrix
Returns the linear index of matrix element.
index - Variable in class smile.math.matrix.SparseMatrix.Entry
The index to the matrix storage.
index - Variable in class smile.neighbor.Neighbor
The index of neighbor object in the dataset.
index - Variable in class smile.util.IntSet
Map of values to index.
IndexDataFrame - Class in smile.data
A data frame with a new index instead of the default [0, n) row index.
IndexDataFrame(DataFrame, int[]) - Constructor for class smile.data.IndexDataFrame
Constructor.
indexOf(int[]) - Method in class smile.classification.ClassLabels
Maps the class labels to index.
indexOf(int) - Method in class smile.util.IntSet
Maps the value to index.
infer(String) - Static method in interface smile.data.type.DataType
Infers the type of a string.
inferSchema(Reader, int) - Method in class smile.io.CSV
Infer the schema from the top n rows.
inferSchema(BufferedReader, int) - Method in class smile.io.JSON
Infer the schema from the top n objects.
info - Variable in class smile.math.matrix.BandMatrix.LU
If info = 0, the LU decomposition was successful.
info - Variable in class smile.math.matrix.FloatBandMatrix.LU
If info = 0, the LU decomposition was successful.
info - Variable in class smile.math.matrix.FloatMatrix.LU
If info = 0, the LU decomposition was successful.
info - Variable in class smile.math.matrix.FloatSymmMatrix.BunchKaufman
If info = 0, the LU decomposition was successful.
info - Variable in class smile.math.matrix.Matrix.LU
If info = 0, the LU decomposition was successful.
info - Variable in class smile.math.matrix.SymmMatrix.BunchKaufman
If info = 0, the LU decomposition was successful.
initHashTable(int, int, int, double, int) - Method in class smile.neighbor.LSH
Initialize the hash tables.
initHashTable(int, int, int, double, int) - Method in class smile.neighbor.MPLSH
 
Input - Interface in smile.io
Static methods that return the InputStream/Reader of a file or URL.
insert(int) - Method in class smile.util.PriorityQueue
Insert a new item into queue.
Instance<T> - Interface in smile.data
An immutable instance.
instance - Static variable in class smile.feature.SignalNoiseRatio
 
instance - Static variable in class smile.feature.SumSquaresRatio
 
instance - Static variable in class smile.validation.Accuracy
 
instance - Static variable in class smile.validation.AdjustedRandIndex
 
instance - Static variable in class smile.validation.Error
 
instance - Static variable in class smile.validation.Fallout
 
instance - Static variable in class smile.validation.FDR
 
instance - Static variable in class smile.validation.MCC
 
instance - Static variable in class smile.validation.MeanAbsoluteDeviation
 
instance - Static variable in class smile.validation.MSE
 
instance - Static variable in class smile.validation.MutualInformation
 
instance - Static variable in class smile.validation.Precision
 
instance - Static variable in class smile.validation.RandIndex
 
instance - Static variable in class smile.validation.Recall
 
instance - Static variable in class smile.validation.RMSE
 
instance - Static variable in class smile.validation.RSS
 
instance - Static variable in class smile.validation.Sensitivity
 
instance - Static variable in class smile.validation.Specificity
 
instances() - Method in class smile.base.svm.KernelMachine
Returns the instances of kernel machines.
IntArray2D - Class in smile.util
2-dimensional array of integers.
IntArray2D(int[][]) - Constructor for class smile.util.IntArray2D
Constructor.
IntArray2D(int, int) - Constructor for class smile.util.IntArray2D
Constructor of all-zero matrix.
IntArray2D(int, int, int) - Constructor for class smile.util.IntArray2D
Constructor.
IntArray2D(int, int, int[]) - Constructor for class smile.util.IntArray2D
Constructor.
IntArrayList - Class in smile.util
A resizeable, array-backed list of integer primitives.
IntArrayList() - Constructor for class smile.util.IntArrayList
Constructs an empty list.
IntArrayList(int) - Constructor for class smile.util.IntArrayList
Constructs an empty list with the specified initial capacity.
IntArrayList(int[]) - Constructor for class smile.util.IntArrayList
Constructs a list containing the values of the specified array.
IntDoubleHashMap - Class in smile.util
HashMap<int, double> for primitive types.
IntDoubleHashMap() - Constructor for class smile.util.IntDoubleHashMap
Constructs an empty HashMap with the default initial capacity (16) and the default load factor (0.75).
IntDoubleHashMap(int, float) - Constructor for class smile.util.IntDoubleHashMap
Constructor.
INTEGER - Static variable in class smile.swing.table.NumberCellRenderer
 
IntegerArrayCellEditor - Class in smile.swing.table
Implements a cell editor that uses a formatted text field to edit int[] values.
IntegerArrayCellEditor() - Constructor for class smile.swing.table.IntegerArrayCellEditor
Constructor.
IntegerArrayCellRenderer - Class in smile.swing.table
Integer array renderer in JTable.
IntegerArrayCellRenderer() - Constructor for class smile.swing.table.IntegerArrayCellRenderer
Constructor.
IntegerArrayType - Static variable in class smile.data.type.DataTypes
Integer Array data type.
IntegerCellEditor - Class in smile.swing.table
Implements a cell editor that uses a formatted text field to edit Integer values.
IntegerCellEditor() - Constructor for class smile.swing.table.IntegerCellEditor
Constructor.
IntegerCellEditor(int, int) - Constructor for class smile.swing.table.IntegerCellEditor
Constructor.
IntegerObjectType - Static variable in class smile.data.type.DataTypes
Integer Object data type.
IntegerType - Static variable in class smile.data.type.DataTypes
Integer data type.
IntegerType - Class in smile.data.type
Integer data type.
interact(String...) - Static method in interface smile.data.formula.Terms
Factor interaction of two or more factors.
intercept(double[]) - Method in interface smile.base.cart.Loss
Returns the intercept of model.
intercept() - Method in class smile.base.svm.KernelMachine
Returns the intercept.
intercept() - Method in class smile.regression.LinearModel
Returns the intercept.
intercept() - Method in class smile.timeseries.AR
Returns the intercept.
intercept() - Method in class smile.timeseries.ARMA
Returns the intercept.
InternalNode - Class in smile.base.cart
An internal node in CART.
InternalNode(int, double, double, Node, Node) - Constructor for class smile.base.cart.InternalNode
 
interpolate(double) - Method in class smile.interpolation.AbstractInterpolation
 
interpolate(double, double) - Method in class smile.interpolation.BicubicInterpolation
 
interpolate(double, double) - Method in class smile.interpolation.BilinearInterpolation
 
interpolate(double, double) - Method in class smile.interpolation.CubicSplineInterpolation2D
 
interpolate(double) - Method in interface smile.interpolation.Interpolation
Given a value x, return an interpolated value.
interpolate(double, double) - Method in interface smile.interpolation.Interpolation2D
Interpolate the data at a given 2-dimensional point.
interpolate(double...) - Method in class smile.interpolation.KrigingInterpolation
Interpolate the function at given point.
interpolate(double) - Method in class smile.interpolation.KrigingInterpolation1D
 
interpolate(double, double) - Method in class smile.interpolation.KrigingInterpolation2D
 
interpolate(double[][]) - Static method in class smile.interpolation.LaplaceInterpolation
Laplace interpolation.
interpolate(double[][], double) - Static method in class smile.interpolation.LaplaceInterpolation
Laplace interpolation.
interpolate(double[][], double, int) - Static method in class smile.interpolation.LaplaceInterpolation
Laplace interpolation.
interpolate(double...) - Method in class smile.interpolation.RBFInterpolation
Interpolate the function at given point.
interpolate(double) - Method in class smile.interpolation.RBFInterpolation1D
 
interpolate(double, double) - Method in class smile.interpolation.RBFInterpolation2D
 
interpolate(double...) - Method in class smile.interpolation.ShepardInterpolation
Interpolate the function at given point.
interpolate(double) - Method in class smile.interpolation.ShepardInterpolation1D
 
interpolate(double, double) - Method in class smile.interpolation.ShepardInterpolation2D
 
Interpolation - Interface in smile.interpolation
In numerical analysis, interpolation is a method of constructing new data points within the range of a discrete set of known data points.
Interpolation2D - Interface in smile.interpolation
Interpolation of 2-dimensional data.
IntervalScale - Class in smile.data.measure
The interval scale allows for the degree of difference between items, but not the ratio between them.
IntervalScale(NumberFormat) - Constructor for class smile.data.measure.IntervalScale
Constructor.
IntFunction - Class in smile.data.formula
The generic term of applying an integer function.
IntFunction(String, Term, IntFunction) - Constructor for class smile.data.formula.IntFunction
Constructor.
IntFunction - Interface in smile.math
An interface representing a univariate int function.
IntHashSet - Class in smile.util
HashSet for primitive types.
IntHashSet() - Constructor for class smile.util.IntHashSet
Constructs an empty HashSet with the default initial capacity (16) and the default load factor (0.75).
IntHashSet(int, float) - Constructor for class smile.util.IntHashSet
Constructor.
IntHeapSelect - Class in smile.sort
This class tracks the smallest values seen thus far in a stream of values.
IntHeapSelect(int) - Constructor for class smile.sort.IntHeapSelect
Constructor.
IntHeapSelect(int[]) - Constructor for class smile.sort.IntHeapSelect
Constructor.
IntPair - Class in smile.util
A pair of integer.
IntPair(int, int) - Constructor for class smile.util.IntPair
Constructor.
IntPattern - Static variable in interface smile.data.type.DataType
Regex for integer.
IntSet - Class in smile.util
A set of integers.
IntSet(int[]) - Constructor for class smile.util.IntSet
Constructor.
intVector(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
intVector(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
intVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
intVector(int) - Method in class smile.data.IndexDataFrame
 
IntVector - Interface in smile.data.vector
An immutable integer vector.
inverf(double) - Static method in class smile.math.special.Erf
The inverse error function.
inverfc(double) - Static method in class smile.math.special.Erf
The inverse complementary error function.
inverse() - Method in class smile.math.matrix.BandMatrix.Cholesky
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.BandMatrix.LU
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.FloatBandMatrix.Cholesky
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.FloatBandMatrix.LU
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.FloatMatrix.Cholesky
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.FloatMatrix
Returns the inverse matrix.
inverse() - Method in class smile.math.matrix.FloatMatrix.LU
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.FloatSymmMatrix.BunchKaufman
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.FloatSymmMatrix.Cholesky
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.Matrix.Cholesky
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.Matrix
Returns the inverse matrix.
inverse() - Method in class smile.math.matrix.Matrix.LU
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.SymmMatrix.BunchKaufman
Returns the matrix inverse.
inverse() - Method in class smile.math.matrix.SymmMatrix.Cholesky
Returns the matrix inverse.
inverse(double, double) - Static method in interface smile.math.TimeFunction
Returns the inverse decay function initLearningRate / (1 + decayRate * t / decaySteps).
inverse(double, int, double) - Static method in interface smile.math.TimeFunction
Returns the inverse decay function.
inverse(double, int, double, boolean) - Static method in interface smile.math.TimeFunction
Returns the inverse decay function initLearningRate / (1 + decayRate * t / decaySteps).
inverse(double[]) - Method in class smile.wavelet.Wavelet
Inverse discrete wavelet transform.
InverseMultiquadricRadialBasis - Class in smile.math.rbf
Inverse multiquadric RBF.
InverseMultiquadricRadialBasis() - Constructor for class smile.math.rbf.InverseMultiquadricRadialBasis
 
InverseMultiquadricRadialBasis(double) - Constructor for class smile.math.rbf.InverseMultiquadricRadialBasis
 
inverseRegularizedIncompleteBetaFunction(double, double, double) - Static method in class smile.math.special.Beta
Inverse of regularized incomplete beta function.
inverseRegularizedIncompleteGamma(double, double) - Static method in class smile.math.special.Gamma
The inverse of regularized incomplete gamma function.
inverseTransformSampling() - Method in class smile.stat.distribution.AbstractDistribution
Use inverse transform sampling (also known as the inverse probability integral transform or inverse transformation method or Smirnov transform) to draw a sample from the given distribution.
invlink(double) - Method in interface smile.glm.model.Model
The inverse of link function.
ipiv - Variable in class smile.math.matrix.BandMatrix.LU
The pivot vector.
ipiv - Variable in class smile.math.matrix.FloatBandMatrix.LU
The pivot vector.
ipiv - Variable in class smile.math.matrix.FloatMatrix.LU
The pivot vector.
ipiv - Variable in class smile.math.matrix.FloatSymmMatrix.BunchKaufman
The pivot vector.
ipiv - Variable in class smile.math.matrix.Matrix.LU
The pivot vector.
ipiv - Variable in class smile.math.matrix.SymmMatrix.BunchKaufman
The pivot vector.
IQAgent - Class in smile.sort
Incremental quantile estimation.
IQAgent() - Constructor for class smile.sort.IQAgent
Constructor.
IQAgent(int) - Constructor for class smile.sort.IQAgent
Constructor.
isAncestorOf(Concept) - Method in class smile.taxonomy.Concept
Returns true if this concept is an ancestor of the given concept.
isBoolean() - Method in class smile.data.type.BooleanType
 
isBoolean() - Method in interface smile.data.type.DataType
Returns true if the type is boolean or Boolean.
isBoolean() - Method in class smile.data.type.ObjectType
 
isByte() - Method in class smile.data.type.ByteType
 
isByte() - Method in interface smile.data.type.DataType
Returns true if the type is byte or Byte.
isByte() - Method in class smile.data.type.ObjectType
 
isCellEditable(int, int) - Method in class smile.swing.Table.RowHeader
Don't edit data in the main TableModel by mistake
isChar() - Method in class smile.data.type.CharType
 
isChar() - Method in interface smile.data.type.DataType
Returns true if the type is char or Char.
isChar() - Method in class smile.data.type.ObjectType
 
isDouble() - Method in interface smile.data.type.DataType
Returns true if the type is double or Double.
isDouble(DataType) - Static method in interface smile.data.type.DataType
Returns true if the given type is of double, either primitive or boxed.
isDouble() - Method in class smile.data.type.DoubleType
 
isDouble() - Method in class smile.data.type.ObjectType
 
isEmpty() - Method in interface smile.data.Dataset
Returns true if the dataset is empty.
isEmpty() - Method in class smile.plot.swing.Isoline
Returns true if the isoline doesn't have any points.
isEmpty() - Method in class smile.util.DoubleArrayList
Returns true if this list contains no values.
isEmpty() - Method in class smile.util.IntArrayList
Returns true if this list contains no values.
isEmpty() - Method in class smile.util.SparseArray
Returns true if the array is empty.
isExpandable() - Method in class smile.neighbor.lsh.Probe
 
isExtendable() - Method in class smile.neighbor.lsh.Probe
 
isFloat() - Method in interface smile.data.type.DataType
Returns true if the type is float or Float.
isFloat(DataType) - Static method in interface smile.data.type.DataType
Returns true if the given type is of float, either primitive or boxed.
isFloat() - Method in class smile.data.type.FloatType
 
isFloat() - Method in class smile.data.type.ObjectType
 
isFloating() - Method in interface smile.data.type.DataType
Returns true if the type is float or double.
isFrameVisible() - Method in class smile.plot.swing.Axis
Returns the visibility of the frame grid lines and their labels.
isGridVisible() - Method in class smile.plot.swing.Axis
Returns the visibility of the grid lines and their labels.
isInt() - Method in interface smile.data.type.DataType
Returns true if the type is int or Integer.
isInt(DataType) - Static method in interface smile.data.type.DataType
Returns true if the given type is of int, short, byte, char, either primitive or boxed.
isInt() - Method in class smile.data.type.IntegerType
 
isInt() - Method in class smile.data.type.ObjectType
 
isInt(float) - Static method in class smile.math.MathEx
Returns true if x is an integer.
isInt(double) - Static method in class smile.math.MathEx
Returns true if x is an integer.
isIntegral() - Method in interface smile.data.type.DataType
Returns true if the type is int, long, short or byte.
isLeaf() - Method in class smile.taxonomy.Concept
Check if a node is a leaf in the taxonomy tree.
isLegendVisible() - Method in class smile.plot.swing.Canvas
Returns true if legends are visible.
isLong() - Method in interface smile.data.type.DataType
Returns true if the type is long or Long.
isLong(DataType) - Static method in interface smile.data.type.DataType
Returns true if the given type is of long, either primitive or boxed.
isLong() - Method in class smile.data.type.LongType
 
isLong() - Method in class smile.data.type.ObjectType
 
isNormalized() - Method in class smile.classification.RBFNetwork
Returns true if the model is normalized.
isNormalized() - Method in class smile.regression.RBFNetwork
Returns true if the model is normalized.
isNullAt(int, int) - Method in interface smile.data.DataFrame
Checks whether the value at position (i, j) is null.
isNullAt(int, String) - Method in interface smile.data.DataFrame
Checks whether the field value is null.
isNullAt(int) - Method in interface smile.data.Tuple
Checks whether the value at position i is null.
isNullAt(String) - Method in interface smile.data.Tuple
Checks whether the field value is null.
isNullAt(int) - Method in interface smile.data.vector.Vector
Checks whether the value at position i is null.
isNullOrEmpty(String) - Static method in interface smile.util.Strings
Returns true if the string is null or empty.
isNumeric() - Method in interface smile.data.type.DataType
Returns true if the type is numeric (integral or floating).
isNumeric() - Method in class smile.data.type.StructField
Returns true if the field is of integer or floating but not nominal scale.
ISO8601 - Static variable in class smile.swing.table.DateCellEditor
 
ISO8601 - Static variable in class smile.swing.table.DateCellRenderer
 
isObject() - Method in interface smile.data.type.DataType
Returns true if the type is ObjectType.
isObject() - Method in class smile.data.type.ObjectType
 
isObject() - Method in class smile.data.type.StringType
 
Isoline - Class in smile.plot.swing
Contour contains a list of segments.
Isoline(double, boolean) - Constructor for class smile.plot.swing.Isoline
Constructor.
IsoMap - Class in smile.manifold
Isometric feature mapping.
IsoMap(int[], double[][], AdjacencyList) - Constructor for class smile.manifold.IsoMap
Constructor.
IsotonicMDS - Class in smile.mds
Kruskal's nonmetric MDS.
IsotonicMDS(double, double[][]) - Constructor for class smile.mds.IsotonicMDS
Constructor.
IsotonicRegressionScaling - Class in smile.classification
A method to calibrate decision function value to probability.
IsotonicRegressionScaling(double[], double[]) - Constructor for class smile.classification.IsotonicRegressionScaling
Constructor.
isPower2(int) - Static method in class smile.math.MathEx
Returns true if x is a power of 2.
isPrimitive() - Method in interface smile.data.type.DataType
Returns true if this is a primitive data type.
isProbablePrime(long, int) - Static method in class smile.math.MathEx
Returns true if n is probably prime, false if it's definitely composite.
isShiftable() - Method in class smile.neighbor.lsh.Probe
 
isShort() - Method in interface smile.data.type.DataType
Returns true if the type is short or Shorter.
isShort() - Method in class smile.data.type.ObjectType
 
isShort() - Method in class smile.data.type.ShortType
 
isSingular() - Method in class smile.math.matrix.BandMatrix.LU
Returns if the matrix is singular.
isSingular() - Method in class smile.math.matrix.FloatBandMatrix.LU
Returns if the matrix is singular.
isSingular() - Method in class smile.math.matrix.FloatMatrix.LU
Returns if the matrix is singular.
isSingular() - Method in class smile.math.matrix.FloatSymmMatrix.BunchKaufman
Returns if the matrix is singular.
isSingular() - Method in class smile.math.matrix.Matrix.LU
Returns if the matrix is singular.
isSingular() - Method in class smile.math.matrix.SymmMatrix.BunchKaufman
Returns if the matrix is singular.
isString() - Method in interface smile.data.type.DataType
Returns true if the type is String.
isString() - Method in class smile.data.type.StringType
 
isSubmatrix() - Method in class smile.math.matrix.FloatMatrix
Returns if the matrix is a submatrix.
isSubmatrix() - Method in class smile.math.matrix.Matrix
Returns if the matrix is a submatrix.
isSymmetric() - Method in class smile.math.matrix.BandMatrix
Return if the matrix is symmetric (uplo != null).
isSymmetric() - Method in class smile.math.matrix.FloatBandMatrix
Return if the matrix is symmetric (uplo != null).
isSymmetric() - Method in class smile.math.matrix.FloatMatrix
Return if the matrix is symmetric (uplo != null && diag == null).
isSymmetric() - Method in class smile.math.matrix.Matrix
Return if the matrix is symmetric (uplo != null && diag == null).
isTickVisible() - Method in class smile.plot.swing.Axis
Returns the visibility of the axis label.
isVariable() - Method in interface smile.data.formula.Feature
Returns true if the term represents a plain variable/column in the data frame.
isZero(float) - Static method in class smile.math.MathEx
Tests if a floating number is zero.
isZero(float, float) - Static method in class smile.math.MathEx
Tests if a floating number is zero with given epsilon.
isZero(double) - Static method in class smile.math.MathEx
Tests if a floating number is zero.
isZero(double, double) - Static method in class smile.math.MathEx
Tests if a floating number is zero with given epsilon.
items - Variable in class smile.association.ItemSet
The set of items.
ItemSet - Class in smile.association
A set of items.
ItemSet(int[], int) - Constructor for class smile.association.ItemSet
Constructor.
iterator() - Method in class smile.association.ARM
 
iterator() - Method in class smile.association.FPGrowth
 
iterator() - Method in class smile.data.IndexDataFrame
 
iterator() - Method in class smile.math.matrix.FloatSparseMatrix
Returns an iterator of nonzero entries.
iterator(int, int) - Method in class smile.math.matrix.FloatSparseMatrix
Returns an iterator of nonzero entries.
iterator() - Method in class smile.math.matrix.SparseMatrix
Returns an iterator of nonzero entries.
iterator(int, int) - Method in class smile.math.matrix.SparseMatrix
Returns an iterator of nonzero entries.
iterator() - Method in interface smile.nlp.dictionary.Dictionary
Returns an iterator over the elements in this dictionary.
iterator() - Method in enum smile.nlp.dictionary.EnglishDictionary
 
iterator() - Method in class smile.nlp.dictionary.EnglishPunctuations
 
iterator() - Method in enum smile.nlp.dictionary.EnglishStopWords
 
iterator() - Method in class smile.nlp.dictionary.SimpleDictionary
 
iterator() - Method in class smile.util.SparseArray
Returns an iterator of nonzero entries.

J

j - Variable in class smile.math.matrix.FloatSparseMatrix.Entry
The column index.
j - Variable in class smile.math.matrix.SparseMatrix.Entry
The column index.
j - Variable in class smile.util.IntPair
 
JaccardDistance<T> - Class in smile.math.distance
The Jaccard index, also known as the Jaccard similarity coefficient is a statistic used for comparing the similarity and diversity of sample sets.
JaccardDistance() - Constructor for class smile.math.distance.JaccardDistance
Constructor.
Jacobi(DMatrix) - Static method in class smile.math.matrix.BiconjugateGradient
Returns a simple preconditioner matrix that is the trivial diagonal part of A in some cases.
JensenShannonDistance - Class in smile.math.distance
The Jensen-Shannon divergence is a popular method of measuring the similarity between two probability distributions.
JensenShannonDistance() - Constructor for class smile.math.distance.JensenShannonDistance
Constructor.
JensenShannonDivergence(double[], double[]) - Static method in class smile.math.MathEx
Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.
JensenShannonDivergence(SparseArray, SparseArray) - Static method in class smile.math.MathEx
Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.
JensenShannonDivergence(double[], SparseArray) - Static method in class smile.math.MathEx
Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.
JensenShannonDivergence(SparseArray, double[]) - Static method in class smile.math.MathEx
Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.
jet(int) - Static method in interface smile.plot.swing.Palette
Generate jet color palette.
jet(int, float) - Static method in interface smile.plot.swing.Palette
Generate jet color palette.
joint(int[], int[]) - Static method in class smile.validation.NormalizedMutualInformation
Calculates the normalized mutual information of I(y1, y2) / H(y1, y2).
JSON - Class in smile.io
Reads JSON datasets.
JSON() - Constructor for class smile.io.JSON
Constructor.
json(String) - Static method in interface smile.io.Read
Reads a JSON file.
json(String, JSON.Mode, StructType) - Static method in interface smile.io.Read
Reads a JSON file.
json(Path) - Static method in interface smile.io.Read
Reads a JSON file.
json(Path, JSON.Mode, StructType) - Static method in interface smile.io.Read
Reads a JSON file.
JSON.Mode - Enum in smile.io
JSON files in single-line or multi-line mode.

K

k - Variable in class smile.classification.ClassLabels
The number of classes.
k - Variable in class smile.clustering.PartitionClustering
The number of clusters.
k(int[], int[]) - Method in class smile.math.kernel.BinarySparseGaussianKernel
 
k(int[], int[]) - Method in class smile.math.kernel.BinarySparseHyperbolicTangentKernel
 
k(int[], int[]) - Method in class smile.math.kernel.BinarySparseLaplacianKernel
 
k(int[], int[]) - Method in class smile.math.kernel.BinarySparseLinearKernel
 
k(int[], int[]) - Method in class smile.math.kernel.BinarySparsePolynomialKernel
 
k(int[], int[]) - Method in class smile.math.kernel.BinarySparseThinPlateSplineKernel
 
k(double[], double[]) - Method in class smile.math.kernel.GaussianKernel
 
k(double[], double[]) - Method in class smile.math.kernel.HellingerKernel
 
k(double[], double[]) - Method in class smile.math.kernel.HyperbolicTangentKernel
 
k(double[], double[]) - Method in class smile.math.kernel.LaplacianKernel
 
k(double[], double[]) - Method in class smile.math.kernel.LinearKernel
 
k(T, T) - Method in interface smile.math.kernel.MercerKernel
Kernel function.
k(double[], double[]) - Method in class smile.math.kernel.PearsonKernel
 
k(double[], double[]) - Method in class smile.math.kernel.PolynomialKernel
 
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseGaussianKernel
 
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseHyperbolicTangentKernel
 
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseLaplacianKernel
 
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseLinearKernel
 
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparsePolynomialKernel
 
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseThinPlateSplineKernel
 
k(double[], double[]) - Method in class smile.math.kernel.ThinPlateSplineKernel
 
k - Variable in class smile.neighbor.LSH
The number of random projections per hash value.
k - Variable in class smile.stat.distribution.GammaDistribution
The shape parameter.
k - Variable in class smile.stat.distribution.WeibullDistribution
The shape parameter.
k - Variable in class smile.validation.Bootstrap
The number of rounds of cross validation.
k - Variable in class smile.validation.CrossValidation
The number of rounds of cross validation.
k - Variable in class smile.validation.GroupKFold
The number of folds.
KDTree<E> - Class in smile.neighbor
A KD-tree (short for k-dimensional tree) is a space-partitioning dataset structure for organizing points in a k-dimensional space.
KDTree(double[][], E[]) - Constructor for class smile.neighbor.KDTree
Constructor.
kendall(int[], int[]) - Static method in class smile.math.MathEx
The Kendall Tau Rank Correlation Coefficient is used to measure the degree of correspondence between sets of rankings where the measures are not equidistant.
kendall(float[], float[]) - Static method in class smile.math.MathEx
The Kendall Tau Rank Correlation Coefficient is used to measure the degree of correspondence between sets of rankings where the measures are not equidistant.
kendall(double[], double[]) - Static method in class smile.math.MathEx
The Kendall Tau Rank Correlation Coefficient is used to measure the degree of correspondence between sets of rankings where the measures are not equidistant.
kendall(double[], double[]) - Static method in class smile.stat.hypothesis.CorTest
Kendall rank correlation test.
kernel() - Method in class smile.base.svm.KernelMachine
Returns the kernel function.
KernelDensity - Class in smile.stat.distribution
Kernel density estimation is a non-parametric way of estimating the probability density function of a random variable.
KernelDensity(double[]) - Constructor for class smile.stat.distribution.KernelDensity
Constructor.
KernelDensity(double[], double) - Constructor for class smile.stat.distribution.KernelDensity
Constructor.
KernelMachine<T> - Class in smile.base.svm
Kernel machines.
KernelMachine(MercerKernel<T>, T[], double[]) - Constructor for class smile.base.svm.KernelMachine
Constructor.
KernelMachine(MercerKernel<T>, T[], double[], double) - Constructor for class smile.base.svm.KernelMachine
Constructor.
KernelMachine<T> - Class in smile.regression
The learning methods building on kernels.
KernelMachine(MercerKernel<T>, T[], double[]) - Constructor for class smile.regression.KernelMachine
Constructor.
KernelMachine(MercerKernel<T>, T[], double[], double) - Constructor for class smile.regression.KernelMachine
Constructor.
key - Variable in class smile.neighbor.Neighbor
The key of neighbor.
keys - Variable in class smile.neighbor.LSH
The keys of data objects.
keys() - Method in class smile.neighbor.MutableLSH
Returns the keys.
kl() - Method in class smile.math.matrix.BandMatrix
Returns the number of subdiagonals.
kl() - Method in class smile.math.matrix.FloatBandMatrix
Returns the number of subdiagonals.
KMeans - Class in smile.clustering
K-Means clustering.
KMeans(double, double[][], int[]) - Constructor for class smile.clustering.KMeans
Constructor.
KMeansImputation - Class in smile.imputation
Missing value imputation by K-Means clustering.
KMeansImputation(int) - Constructor for class smile.imputation.KMeansImputation
Constructor.
KMeansImputation(int, int) - Constructor for class smile.imputation.KMeansImputation
Constructor.
KModes - Class in smile.clustering
K-Modes clustering.
KModes(double, int[][], int[]) - Constructor for class smile.clustering.KModes
Constructor.
KNN<T> - Class in smile.classification
K-nearest neighbor classifier.
KNN(KNNSearch<T, T>, int[], int) - Constructor for class smile.classification.KNN
Constructor.
knn(E, int) - Method in class smile.neighbor.CoverTree
 
knn(double[], int) - Method in class smile.neighbor.KDTree
 
knn(K, int) - Method in interface smile.neighbor.KNNSearch
Search the k nearest neighbors to the query.
knn(T, int) - Method in class smile.neighbor.LinearSearch
 
knn(double[], int) - Method in class smile.neighbor.LSH
 
knn(double[], int) - Method in class smile.neighbor.MPLSH
 
knn(double[], int, double, int) - Method in class smile.neighbor.MPLSH
Returns the approximate k-nearest neighbors.
KNNImputation - Class in smile.imputation
Missing value imputation by k-nearest neighbors.
KNNImputation(int) - Constructor for class smile.imputation.KNNImputation
Constructor.
KNNSearch<K,V> - Interface in smile.neighbor
K-nearest neighbor search identifies the top k nearest neighbors to the query.
KPCA<T> - Class in smile.projection
Kernel principal component analysis.
KPCA(T[], MercerKernel<T>, double[], double, double[][], double[], Matrix) - Constructor for class smile.projection.KPCA
Constructor.
KrigingInterpolation - Class in smile.interpolation
Kriging interpolation for the data points irregularly distributed in space.
KrigingInterpolation(double[][], double[]) - Constructor for class smile.interpolation.KrigingInterpolation
Constructor.
KrigingInterpolation(double[][], double[], Variogram, double[]) - Constructor for class smile.interpolation.KrigingInterpolation
Constructor.
KrigingInterpolation1D - Class in smile.interpolation
Kriging interpolation for the data points irregularly distributed in space.
KrigingInterpolation1D(double[], double[]) - Constructor for class smile.interpolation.KrigingInterpolation1D
Constructor.
KrigingInterpolation1D(double[], double[], double) - Constructor for class smile.interpolation.KrigingInterpolation1D
Constructor.
KrigingInterpolation2D - Class in smile.interpolation
Kriging interpolation for the data points irregularly distributed in space.
KrigingInterpolation2D(double[], double[], double[]) - Constructor for class smile.interpolation.KrigingInterpolation2D
Constructor.
KrigingInterpolation2D(double[], double[], double[], double) - Constructor for class smile.interpolation.KrigingInterpolation2D
Constructor.
KSTest - Class in smile.stat.hypothesis
The Kolmogorov-Smirnov test (K-S test) is a form of minimum distance estimation used as a non-parametric test of equality of one-dimensional probability distributions.
ku() - Method in class smile.math.matrix.BandMatrix
Returns the number of superdiagonals.
ku() - Method in class smile.math.matrix.FloatBandMatrix
Returns the number of superdiagonals.
KullbackLeiblerDivergence(double[], double[]) - Static method in class smile.math.MathEx
Kullback-Leibler divergence.
KullbackLeiblerDivergence(SparseArray, SparseArray) - Static method in class smile.math.MathEx
Kullback-Leibler divergence.
KullbackLeiblerDivergence(double[], SparseArray) - Static method in class smile.math.MathEx
Kullback-Leibler divergence.
KullbackLeiblerDivergence(SparseArray, double[]) - Static method in class smile.math.MathEx
Kullback-Leibler divergence.
Kurtosis - Class in smile.projection.ica
The kurtosis of the probability density function of a signal.
Kurtosis() - Constructor for class smile.projection.ica.Kurtosis
 

L

L - Variable in class smile.stat.distribution.DiscreteExponentialFamilyMixture
The log-likelihood when the distribution is fit on a sample data.
L - Variable in class smile.stat.distribution.ExponentialFamilyMixture
The log-likelihood when the distribution is fit on a sample data.
L - Variable in class smile.stat.distribution.MultivariateExponentialFamilyMixture
The log-likelihood when the distribution is fit on a sample data.
L - Variable in class smile.vq.BIRCH
The number of CF entries in the leaf nodes.
label() - Method in interface smile.data.Instance
Returns the class label of instance.
Label - Class in smile.plot.swing
Label is a single line text.
Label(String, double[], double, double, double, Font, Color) - Constructor for class smile.plot.swing.Label
Constructor.
labels - Variable in class smile.classification.ClassLabels
The class labels.
lad() - Static method in interface smile.base.cart.Loss
Least absolute deviation regression.
LamarckianChromosome - Interface in smile.gap
Artificial chromosomes used in Lamarckian algorithm that is a hybrid of of evolutionary computation and a local improver such as hill-climbing.
lambda - Variable in class smile.base.mlp.MultilayerPerceptron
The L2 regularization factor, which is also the weight decay factor.
lambda - Variable in class smile.stat.distribution.ExponentialDistribution
The rate parameter.
lambda - Variable in class smile.stat.distribution.PoissonDistribution
The average number of events per interval.
lambda - Variable in class smile.stat.distribution.WeibullDistribution
The scale parameter.
LancasterStemmer - Class in smile.nlp.stemmer
The Paice/Husk Lancaster stemming algorithm.
LancasterStemmer() - Constructor for class smile.nlp.stemmer.LancasterStemmer
Constructor with default rules.
LancasterStemmer(boolean) - Constructor for class smile.nlp.stemmer.LancasterStemmer
Constructor with default rules.
LancasterStemmer(InputStream) - Constructor for class smile.nlp.stemmer.LancasterStemmer
Constructor with customized rules.
LancasterStemmer(InputStream, boolean) - Constructor for class smile.nlp.stemmer.LancasterStemmer
Constructor with customized rules.
Lanczos - Class in smile.math.matrix
The Lanczos algorithm is a direct algorithm devised by Cornelius Lanczos that is an adaptation of power methods to find the most useful eigenvalues and eigenvectors of an nth order linear system with a limited number of operations, m, where m is much smaller than n.
Lanczos() - Constructor for class smile.math.matrix.Lanczos
 
lapack() - Method in enum smile.math.blas.Diag
Returns the byte value for LAPACK.
lapack() - Method in enum smile.math.blas.EigenRange
Returns the byte value for LAPACK.
lapack() - Method in enum smile.math.blas.EVDJob
Returns the byte value for LAPACK.
LAPACK - Interface in smile.math.blas
Linear Algebra Package.
lapack() - Method in enum smile.math.blas.Layout
Returns the byte value for LAPACK.
lapack() - Method in enum smile.math.blas.Side
Returns the byte value for LAPACK.
lapack() - Method in enum smile.math.blas.SVDJob
Returns the byte value for LAPACK.
lapack() - Method in enum smile.math.blas.Transpose
Returns the byte value for LAPACK.
lapack() - Method in enum smile.math.blas.UPLO
Returns the byte value for LAPACK.
LaplaceInterpolation - Class in smile.interpolation
Laplace interpolation to restore missing or unmeasured values on a 2-dimensional evenly spaced regular grid.
LaplaceInterpolation() - Constructor for class smile.interpolation.LaplaceInterpolation
 
LaplacianEigenmap - Class in smile.manifold
Laplacian Eigenmap.
LaplacianEigenmap(int[], double[][], AdjacencyList) - Constructor for class smile.manifold.LaplacianEigenmap
Constructor with discrete weights.
LaplacianEigenmap(double, int[], double[][], AdjacencyList) - Constructor for class smile.manifold.LaplacianEigenmap
Constructor with Gaussian kernel.
LaplacianKernel - Class in smile.math.kernel
The Laplacian Kernel.
LaplacianKernel(double) - Constructor for class smile.math.kernel.LaplacianKernel
Constructor.
LASSO - Class in smile.regression
Lasso (least absolute shrinkage and selection operator) regression.
LASSO() - Constructor for class smile.regression.LASSO
 
LASVM<T> - Class in smile.base.svm
LASVM is an approximate SVM solver that uses online approximation.
LASVM(MercerKernel<T>, double, double) - Constructor for class smile.base.svm.LASVM
Constructor.
LASVM(MercerKernel<T>, double, double, double) - Constructor for class smile.base.svm.LASVM
Constructor.
lattice(int, int, double[][]) - Static method in class smile.vq.SOM
Creates a lattice of which the weight vectors are randomly selected from samples.
Layer - Class in smile.base.mlp
A layer in the neural network.
Layer(int, int) - Constructor for class smile.base.mlp.Layer
Constructor.
Layer(Matrix, double[]) - Constructor for class smile.base.mlp.Layer
Constructor.
LayerBuilder - Class in smile.base.mlp
The builder of layers.
LayerBuilder(int) - Constructor for class smile.base.mlp.LayerBuilder
Constructor.
Layout - Enum in smile.math.blas
Matrix layout.
layout() - Method in class smile.math.matrix.BandMatrix
Returns the matrix layout.
layout() - Method in class smile.math.matrix.FloatBandMatrix
Returns the matrix layout.
layout() - Method in class smile.math.matrix.FloatMatrix
Returns the matrix layout.
layout() - Method in class smile.math.matrix.FloatSymmMatrix
Returns the matrix layout.
layout() - Method in class smile.math.matrix.Matrix
Returns the matrix layout.
layout() - Method in class smile.math.matrix.SymmMatrix
Returns the matrix layout.
lchoose(int, int) - Static method in class smile.math.MathEx
The log of n choose k.
ld() - Method in class smile.math.matrix.BandMatrix
Returns the leading dimension.
ld() - Method in class smile.math.matrix.FloatBandMatrix
Returns the leading dimension.
ld() - Method in class smile.math.matrix.FloatMatrix
Returns the leading dimension.
ld() - Method in class smile.math.matrix.Matrix
Returns the leading dimension.
LDA - Class in smile.classification
Linear discriminant analysis.
LDA(double[], double[][], double[], Matrix) - Constructor for class smile.classification.LDA
Constructor.
LDA(double[], double[][], double[], Matrix, IntSet) - Constructor for class smile.classification.LDA
Constructor.
LeafNode - Class in smile.base.cart
A leaf node in decision tree.
LeafNode(int) - Constructor for class smile.base.cart.LeafNode
Constructor.
leafs() - Method in class smile.base.cart.InternalNode
 
leafs() - Method in class smile.base.cart.LeafNode
 
leafs() - Method in interface smile.base.cart.Node
Returns the number of leaf nodes in the subtree.
learningRate - Variable in class smile.base.mlp.MultilayerPerceptron
The learning rate.
LeeDistance - Class in smile.math.distance
In coding theory, the Lee distance is a distance between two strings x1x2...xn and y1y2...yn of equal length n over the q-ary alphabet {0, 1, ..., q-1} of size q ≥ 2, defined as
LeeDistance(int) - Constructor for class smile.math.distance.LeeDistance
Constructor with a given size q of alphabet.
leftPad(String, int, char) - Static method in interface smile.util.Strings
Left pad a String with a specified character.
Legend - Class in smile.plot.swing
Legend is a single line text which coordinates are in proportional to the base coordinates.
Legend(String, Color) - Constructor for class smile.plot.swing.Legend
Constructor.
legends() - Method in class smile.plot.swing.BarPlot
 
legends() - Method in class smile.plot.swing.LinePlot
 
legends() - Method in class smile.plot.swing.Plot
Returns the optional name of shape, which will be used to draw a legend outside the box.
legends() - Method in class smile.plot.swing.ScatterPlot
 
legends() - Method in class smile.plot.swing.ScreePlot
 
length() - Method in interface smile.data.BinarySparseDataset
Returns the number of nonzero entries.
length() - Method in interface smile.data.Tuple
Number of elements in the Tuple.
length() - Method in class smile.data.type.StructType
Returns the number of fields.
length - Variable in class smile.gap.BitString
The length of chromosome.
length() - Method in class smile.gap.BitString
Returns the length of bit string.
length - Variable in class smile.math.Complex.Array
 
length() - Method in class smile.stat.distribution.BernoulliDistribution
 
length() - Method in class smile.stat.distribution.BetaDistribution
 
length() - Method in class smile.stat.distribution.BinomialDistribution
 
length() - Method in class smile.stat.distribution.ChiSquareDistribution
 
length() - Method in class smile.stat.distribution.DiscreteMixture
 
length() - Method in interface smile.stat.distribution.Distribution
The number of parameters of the distribution.
length() - Method in class smile.stat.distribution.EmpiricalDistribution
 
length() - Method in class smile.stat.distribution.ExponentialDistribution
 
length() - Method in class smile.stat.distribution.FDistribution
 
length() - Method in class smile.stat.distribution.GammaDistribution
 
length() - Method in class smile.stat.distribution.GaussianDistribution
 
length() - Method in class smile.stat.distribution.GeometricDistribution
 
length() - Method in class smile.stat.distribution.HyperGeometricDistribution
 
length() - Method in class smile.stat.distribution.KernelDensity
 
length() - Method in class smile.stat.distribution.LogisticDistribution
 
length() - Method in class smile.stat.distribution.LogNormalDistribution
 
length() - Method in class smile.stat.distribution.Mixture
 
length() - Method in interface smile.stat.distribution.MultivariateDistribution
The number of parameters of the distribution.
length() - Method in class smile.stat.distribution.MultivariateGaussianDistribution
 
length() - Method in class smile.stat.distribution.MultivariateMixture
 
length() - Method in class smile.stat.distribution.NegativeBinomialDistribution
 
length() - Method in class smile.stat.distribution.PoissonDistribution
 
length() - Method in class smile.stat.distribution.ShiftedGeometricDistribution
 
length() - Method in class smile.stat.distribution.TDistribution
 
length() - Method in class smile.stat.distribution.WeibullDistribution
 
level(int) - Method in class smile.data.measure.CategoricalMeasure
Returns the level string representation.
levels() - Method in class smile.data.measure.CategoricalMeasure
Returns the levels.
LevenbergMarquardt - Class in smile.math
The Levenberg–Marquardt algorithm.
levenshtein(String, String) - Static method in class smile.math.distance.EditDistance
Levenshtein distance between two strings allows insertion, deletion, or substitution of characters.
levenshtein(char[], char[]) - Static method in class smile.math.distance.EditDistance
Levenshtein distance between two strings allows insertion, deletion, or substitution of characters.
leverage - Variable in class smile.association.AssociationRule
The difference between the probability of the rule and the expected probability if the items were statistically independent.
lfactorial(int) - Static method in class smile.math.MathEx
The log of factorial of n.
lgamma(double) - Static method in class smile.math.special.Gamma
The log of the Gamma function.
lhs(String) - Static method in class smile.data.formula.Formula
Factory method.
lhs(Term) - Static method in class smile.data.formula.Formula
Factory method.
libsvm(String) - Static method in interface smile.io.Read
Reads a libsvm sparse dataset.
libsvm(Path) - Static method in interface smile.io.Read
Reads a libsvm sparse dataset.
libsvm(BufferedReader) - Static method in interface smile.io.Read
Reads a libsvm sparse dataset.
lift - Variable in class smile.association.AssociationRule
How many times more often antecedent and consequent occur together than expected if they were statistically independent.
LIGHT_GRAY - Static variable in interface smile.plot.swing.Palette
 
LIGHT_GREEN - Static variable in interface smile.plot.swing.Palette
 
LIGHT_PURPLE - Static variable in interface smile.plot.swing.Palette
 
LIGHT_SLATE_GRAY - Static variable in interface smile.plot.swing.Palette
 
likelihood(int[]) - Method in class smile.stat.distribution.DiscreteDistribution
The likelihood given a sample set following the distribution.
likelihood(double[]) - Method in interface smile.stat.distribution.Distribution
The likelihood of the sample set following this distribution.
likelihood(double[]) - Method in class smile.stat.distribution.KernelDensity
The likelihood of the samples.
likelihood(double[][]) - Method in interface smile.stat.distribution.MultivariateDistribution
The likelihood of the sample set following this distribution.
Line - Class in smile.plot.swing
This class represents a poly line in the plot.
Line(double[][], Line.Style, char, Color) - Constructor for class smile.plot.swing.Line
Constructor.
Line.Style - Enum in smile.plot.swing
The supported styles of lines.
linear() - Static method in interface smile.base.mlp.ActivationFunction
Linear/Identity function.
linear(int) - Static method in class smile.base.mlp.Layer
Returns a hidden layer with linear activation function.
linear(double, int) - Static method in interface smile.math.TimeFunction
Returns the linear learning rate decay function that ends at 0.0001.
linear(double, int, double) - Static method in interface smile.math.TimeFunction
Returns the linear learning rate decay function that starts with an initial learning rate and reach an end learning rate in the given decay steps..
LinearInterpolation - Class in smile.interpolation
Piecewise linear interpolation.
LinearInterpolation(double[], double[]) - Constructor for class smile.interpolation.LinearInterpolation
Constructor.
LinearKernel - Class in smile.math.kernel
The linear dot product kernel.
LinearKernel() - Constructor for class smile.math.kernel.LinearKernel
Constructor.
LinearKernelMachine - Class in smile.base.svm
Linear kernel machine.
LinearKernelMachine(double[], double) - Constructor for class smile.base.svm.LinearKernelMachine
Constructor.
LinearModel - Class in smile.regression
Linear model.
LinearModel(Formula, StructType, Matrix, double[], double[], double) - Constructor for class smile.regression.LinearModel
Constructor.
LinearProjection - Interface in smile.projection
Linear projection.
LinearSearch<T> - Class in smile.neighbor
Brute force linear nearest neighbor search.
LinearSearch(T[], Distance<T>) - Constructor for class smile.neighbor.LinearSearch
Constructor.
LinearSolver - Interface in smile.math.matrix
The interface of the solver of linear system.
LinePlot - Class in smile.plot.swing
Line plot is a special scatter plot which connects points by straight lines.
LinePlot(Line...) - Constructor for class smile.plot.swing.LinePlot
Constructor.
LinePlot(Line[], Legend[]) - Constructor for class smile.plot.swing.LinePlot
Constructor.
linesearch(MultivariateFunction, double[], double, double[], double[], double[], double) - Static method in interface smile.math.BFGS
Minimize a function along a search direction by find a step which satisfies a sufficient decrease condition and a curvature condition.
link(double) - Method in interface smile.glm.model.Model
The link function.
Linkage - Class in smile.clustering.linkage
A measure of dissimilarity between clusters (i.e.
Linkage(double[][]) - Constructor for class smile.clustering.linkage.Linkage
Initialize the linkage with the lower triangular proximity matrix.
Linkage(int, float[]) - Constructor for class smile.clustering.linkage.Linkage
Initialize the linkage with the lower triangular proximity matrix.
ljung(double[], int) - Static method in class smile.timeseries.BoxTest
Box-Pierce test.
LLE - Class in smile.manifold
Locally Linear Embedding.
LLE(int[], double[][], AdjacencyList) - Constructor for class smile.manifold.LLE
Constructor.
lloyd(double[][], int) - Static method in class smile.clustering.KMeans
The implementation of Lloyd algorithm as a benchmark.
lloyd(double[][], int, int, double) - Static method in class smile.clustering.KMeans
The implementation of Lloyd algorithm as a benchmark.
LLSImputation - Class in smile.imputation
Local least squares missing value imputation.
LLSImputation(int) - Constructor for class smile.imputation.LLSImputation
Constructor.
log(String) - Static method in interface smile.data.formula.Terms
Applies Math.log.
log(Term) - Static method in interface smile.data.formula.Terms
Applies Math.log.
log() - Static method in interface smile.glm.model.Poisson
log link function.
log(double) - Static method in class smile.math.MathEx
Returns natural log without underflow.
log10(String) - Static method in interface smile.data.formula.Terms
Applies Math.log10.
log10(Term) - Static method in interface smile.data.formula.Terms
Applies Math.log10.
log1p(String) - Static method in interface smile.data.formula.Terms
Applies Math.log1p.
log1p(Term) - Static method in interface smile.data.formula.Terms
Applies Math.log1p.
log1pe(double) - Static method in class smile.math.MathEx
Returns natural log(1+exp(x)) without overflow.
log2(String) - Static method in interface smile.data.formula.Terms
Applies MathEx.log2.
log2(Term) - Static method in interface smile.data.formula.Terms
Applies MathEx.log2.
log2(double) - Static method in class smile.math.MathEx
Log of base 2.
LogCosh - Class in smile.projection.ica
A good general-purpose contrast function for ICA.
LogCosh() - Constructor for class smile.projection.ica.LogCosh
 
logger - Static variable in interface smile.math.BFGS
 
logger - Static variable in interface smile.math.matrix.ARPACK
 
logger - Static variable in interface smile.math.matrix.PageRank
 
logger - Static variable in interface smile.math.Root
 
logistic(int[]) - Static method in interface smile.base.cart.Loss
Logistic regression loss for binary classification.
logistic(int, int, int[], double[][]) - Static method in interface smile.base.cart.Loss
Logistic regression loss for multi-class classification.
logistic(double) - Static method in class smile.math.MathEx
Logistic sigmoid function.
LogisticDistribution - Class in smile.stat.distribution
The logistic distribution is a continuous probability distribution whose cumulative distribution function is the logistic function, which appears in logistic regression and feedforward neural networks.
LogisticDistribution(double, double) - Constructor for class smile.stat.distribution.LogisticDistribution
Constructor.
LogisticRegression - Class in smile.classification
Logistic regression.
LogisticRegression(int, double, double, IntSet) - Constructor for class smile.classification.LogisticRegression
Constructor.
LogisticRegression.Binomial - Class in smile.classification
Binomial logistic regression.
LogisticRegression.Multinomial - Class in smile.classification
Multinomial logistic regression.
logit() - Static method in interface smile.glm.model.Bernoulli
logit link function.
logit(int[]) - Static method in interface smile.glm.model.Binomial
logit link function.
loglikelihood() - Method in class smile.classification.LogisticRegression
Returns the log-likelihood of model.
loglikelihood() - Method in class smile.classification.Maxent
Returns the log-likelihood of model.
loglikelihood() - Method in class smile.classification.SparseLogisticRegression
Returns the log-likelihood of model.
loglikelihood - Variable in class smile.glm.GLM
Log-likelihood.
loglikelihood() - Method in class smile.glm.GLM
Returns the log-likelihood of model.
loglikelihood(double[], double[]) - Method in interface smile.glm.model.Model
The log-likelihood function.
logLikelihood(int[]) - Method in class smile.stat.distribution.DiscreteDistribution
The likelihood given a sample set following the distribution.
logLikelihood(double[]) - Method in interface smile.stat.distribution.Distribution
The log likelihood of the sample set following this distribution.
logLikelihood(double[]) - Method in class smile.stat.distribution.KernelDensity
The log likelihood of the samples.
logLikelihood(double[][]) - Method in interface smile.stat.distribution.MultivariateDistribution
The log likelihood of the sample set following this distribution.
LogNormalDistribution - Class in smile.stat.distribution
A log-normal distribution is a probability distribution of a random variable whose logarithm is normally distributed.
LogNormalDistribution(double, double) - Constructor for class smile.stat.distribution.LogNormalDistribution
Constructor.
logp(int[], int[]) - Method in class smile.sequence.HMM
Returns the log joint probability of an observation sequence along a state sequence given this HMM.
logp(int[]) - Method in class smile.sequence.HMM
Returns the logarithm probability of an observation sequence given this HMM.
logp(T[], int[]) - Method in class smile.sequence.HMMLabeler
Returns the log joint probability of an observation sequence along a state sequence.
logp(T[]) - Method in class smile.sequence.HMMLabeler
Returns the logarithm probability of an observation sequence.
logp(int) - Method in class smile.stat.distribution.BernoulliDistribution
 
logp(double) - Method in class smile.stat.distribution.BetaDistribution
 
logp(int) - Method in class smile.stat.distribution.BinomialDistribution
 
logp(double) - Method in class smile.stat.distribution.ChiSquareDistribution
 
logp(int) - Method in class smile.stat.distribution.DiscreteDistribution
The probability mass function in log scale.
logp(double) - Method in class smile.stat.distribution.DiscreteDistribution
 
logp(int) - Method in class smile.stat.distribution.DiscreteMixture
 
logp(double) - Method in interface smile.stat.distribution.Distribution
The density at x in log scale, which may prevents the underflow problem.
logp(int) - Method in class smile.stat.distribution.EmpiricalDistribution
 
logp(double) - Method in class smile.stat.distribution.ExponentialDistribution
 
logp(double) - Method in class smile.stat.distribution.FDistribution
 
logp(double) - Method in class smile.stat.distribution.GammaDistribution
 
logp(double) - Method in class smile.stat.distribution.GaussianDistribution
 
logp(int) - Method in class smile.stat.distribution.GeometricDistribution
 
logp(int) - Method in class smile.stat.distribution.HyperGeometricDistribution
 
logp(double) - Method in class smile.stat.distribution.KernelDensity
 
logp(double) - Method in class smile.stat.distribution.LogisticDistribution
 
logp(double) - Method in class smile.stat.distribution.LogNormalDistribution
 
logp(double) - Method in class smile.stat.distribution.Mixture
 
logp(double[]) - Method in interface smile.stat.distribution.MultivariateDistribution
The density at x in log scale, which may prevents the underflow problem.
logp(double[]) - Method in class smile.stat.distribution.MultivariateGaussianDistribution
 
logp(double[]) - Method in class smile.stat.distribution.MultivariateMixture
 
logp(int) - Method in class smile.stat.distribution.NegativeBinomialDistribution
 
logp(int) - Method in class smile.stat.distribution.PoissonDistribution
 
logp(int) - Method in class smile.stat.distribution.ShiftedGeometricDistribution
 
logp(double) - Method in class smile.stat.distribution.TDistribution
 
logp(double) - Method in class smile.stat.distribution.WeibullDistribution
 
LongArrayCellRenderer - Class in smile.swing.table
Long array renderer in JTable.
LongArrayCellRenderer() - Constructor for class smile.swing.table.LongArrayCellRenderer
Constructor.
LongArrayType - Static variable in class smile.data.type.DataTypes
Long Array data type.
LongObjectType - Static variable in class smile.data.type.DataTypes
Long Object data type.
LongPattern - Static variable in interface smile.data.type.DataType
Regex for long.
LongType - Static variable in class smile.data.type.DataTypes
Long data type.
LongType - Class in smile.data.type
Long data type.
longVector(int) - Method in interface smile.data.DataFrame
Selects column based on the column index.
longVector(String) - Method in interface smile.data.DataFrame
Selects column based on the column name.
longVector(Enum<?>) - Method in interface smile.data.DataFrame
Selects column using an enum value.
longVector(int) - Method in class smile.data.IndexDataFrame
 
LongVector - Interface in smile.data.vector
An immutable long vector.
LOOCV - Class in smile.validation
Leave-one-out cross validation.
LOOCV(int) - Constructor for class smile.validation.LOOCV
Constructor.
Loss - Interface in smile.base.cart
Regression loss function.