Uses of Interface
org.apache.ignite.ml.math.Matrix

Packages that use Matrix

Package	Description
org.apache.ignite.ml.math	Contains main APIs for distributed code algebra.
org.apache.ignite.ml.math.decompositions	Contains matrix decompositions for distributed code algebra.
org.apache.ignite.ml.math.impls.matrix	Contains several matrix implementations.
org.apache.ignite.ml.math.impls.storage.vector	Contains specific implementations for vector storage models.
org.apache.ignite.ml.math.impls.vector	Contains specific implementations for vectors.
org.apache.ignite.ml.math.util	Some math utils.
org.apache.ignite.ml.nn	Contains neural networks and related classes.
org.apache.ignite.ml.nn.initializers	Contains multilayer perceptron parameters initializers.
org.apache.ignite.ml.optimization	Contains implementations of optimization algorithms and related classes.
org.apache.ignite.ml.optimization.updatecalculators	Contains update calculators.

Uses of Matrix in org.apache.ignite.ml.math

Methods in org.apache.ignite.ml.math that return Matrix

Modifier and Type	Method and Description
Matrix	Matrix.assign(double val) Assigns given value to all elements of this matrix.
Matrix	Matrix.assign(double[][] vals) Assigns given values to this matrix.
Matrix	Matrix.assign(IntIntToDoubleFunction fun) Assigns each matrix element to the value generated by given function.
Matrix	Matrix.assign(Matrix mtx) Assigns values from given matrix to this matrix.
Matrix	Matrix.assignColumn(int col, Vector vec) Assigns values from given vector to the specified column in this matrix.
Matrix	Matrix.assignRow(int row, Vector vec) Assigns values from given vector to the specified row in this matrix.
Matrix	Matrix.copy() Clones this matrix.
Matrix	Vector.cross(Vector vec) Gets the cross product of this vector and the other vector.
Matrix	Matrix.divide(double x) Divides each value in this matrix by the argument.
Matrix	Matrix.inverse() Returns the inverse matrix of this matrix
Matrix	Matrix.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	Vector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	Matrix.map(IgniteDoubleFunction<Double> fun) Maps all values in this matrix through a given function.
Matrix	Matrix.map(Matrix mtx, IgniteBiFunction<Double,Double,Double> fun) Maps all values in this matrix through a given function.
Matrix	Matrix.minus(Matrix mtx) Creates new matrix where each value is a difference between corresponding value of this matrix and passed in argument matrix.
Matrix	Matrix.plus(double x) Creates new matrix where each value is a sum of the corresponding value of this matrix and argument value.
Matrix	Matrix.plus(Matrix mtx) Creates new matrix where each value is a sum of corresponding values of this matrix and passed in argument matrix.
Matrix	Matrix.set(int row, int col, double val) Sets given value.
Matrix	Matrix.setColumn(int col, double[] data) Sets values for given column.
Matrix	Matrix.setRow(int row, double[] data) Sets values for given row.
Matrix	Matrix.setX(int row, int col, double val) Sets given value without checking for index bounds.
Matrix	Matrix.swapColumns(int col1, int col2) Swaps two columns in this matrix.
Matrix	Matrix.swapRows(int row1, int row2) Swaps two rows in this matrix.
Matrix	Matrix.times(double x) Creates new matrix containing the product of given value and values in this matrix.
Matrix	Matrix.times(Matrix mtx) Creates new matrix that is the product of multiplying this matrix and the argument matrix.
Matrix	Vector.toMatrix(boolean rowLike) Converts this vector into [N x 1] or [1 x N] matrix where N is this vector cardinality.
Matrix	Vector.toMatrixPlusOne(boolean rowLike, double zeroVal) Converts this vector into [N+1 x 1] or [1 x N+1] matrix where N is this vector cardinality
Matrix	Matrix.transpose() Creates new matrix that is transpose of this matrix.
Matrix	Matrix.viewPart(int[] off, int[] size) Creates new view into this matrix.
Matrix	Matrix.viewPart(int rowOff, int rows, int colOff, int cols) Creates new view into this matrix.

Methods in org.apache.ignite.ml.math with parameters of type Matrix

Modifier and Type	Method and Description
Matrix	Matrix.assign(Matrix mtx) Assigns values from given matrix to this matrix.
static void	Blas.checkCardinality(Matrix a, Vector v) Checks if Matrix A can be multiplied by vector v, if not CardinalityException is thrown.
static void	Blas.gemm(double alpha, Matrix a, Matrix b, double beta, Matrix c) For the moment we have no flags indicating if matrix is transposed or not.
static void	Blas.gemv(double alpha, Matrix a, Vector x, double beta, Vector y) y := alpha * A * x + beta * y.
Matrix	Matrix.map(Matrix mtx, IgniteBiFunction<Double,Double,Double> fun) Maps all values in this matrix through a given function.
Matrix	Matrix.minus(Matrix mtx) Creates new matrix where each value is a difference between corresponding value of this matrix and passed in argument matrix.
Matrix	Matrix.plus(Matrix mtx) Creates new matrix where each value is a sum of corresponding values of this matrix and passed in argument matrix.
static void	Tracer.saveAsCsv(Matrix mtx, String fmt, String filePath) Saves given matrix as CSV file.
static void	Tracer.showAscii(Matrix mtx)
static void	Tracer.showAscii(Matrix mtx, IgniteLogger log, String fmt)
static void	Tracer.showAscii(Matrix mtx, String fmt)
static void	Tracer.showHtml(Matrix mtx) Shows given matrix in the browser with D3-based visualization.
static void	Tracer.showHtml(Matrix mtx, boolean useAsciiFallback) Shows given matrix in the browser with D3-based visualization.
static void	Tracer.showHtml(Matrix mtx, Tracer.ColorMapper cm) Shows given matrix in the browser with D3-based visualization.
static void	Tracer.showHtml(Matrix mtx, Tracer.ColorMapper cm, boolean useAsciiFallback) Shows given matrix in the browser with D3-based visualization.
Matrix	Matrix.times(Matrix mtx) Creates new matrix that is the product of multiplying this matrix and the argument matrix.

Uses of Matrix in org.apache.ignite.ml.math.decompositions

Methods in org.apache.ignite.ml.math.decompositions that return Matrix

Modifier and Type	Method and Description
Matrix	QRDSolver.calculateBetaVariance(int p) Calculates the variance-covariance matrix of the regression parameters.
Matrix	QRDSolver.calculateHat() Compute the "hat" matrix.
protected Matrix	DecompositionSupport.copy(Matrix matrix) Create the copy of matrix with read-only matrices support.
Matrix	EigenDecomposition.getD() Return the block diagonal eigenvalue matrix
Matrix	CholeskyDecomposition.getL() Returns the matrix L of the decomposition.
Matrix	LUDecomposition.getL() Returns the matrix L of the decomposition.
Matrix	CholeskyDecomposition.getLT() Returns the transpose of the matrix L of the decomposition.
Matrix	LUDecomposition.getP() Returns the P rows permutation matrix.
Matrix	QRDecomposition.getQ() Gets orthogonal factor Q.
Matrix	QRDecomposition.getR() Gets triangular factor R.
Matrix	SingularValueDecomposition.getS()
Matrix	SingularValueDecomposition.getU() Gets the left singular vectors U.
Matrix	LUDecomposition.getU() Returns the matrix U of the decomposition.
Matrix	SingularValueDecomposition.getV() Gets the right singular vectors V.
Matrix	EigenDecomposition.getV() Return the eigen vector matrix.
protected Matrix	DecompositionSupport.like(Matrix matrix) Create the like matrix with read-only matrices support.
protected Matrix	DecompositionSupport.like(Matrix matrix, int rows, int cols) Create the like matrix with specified size with read-only matrices support.
Matrix	QRDecomposition.solve(Matrix mtx) Least squares solution of A*X = B; returns X.
Matrix	CholeskyDecomposition.solve(Matrix b) Solve the linear equation A × X = B for matrices A.
Matrix	QRDSolver.solve(Matrix mtx) Least squares solution of A*X = B; returns X.
Matrix	LUDecomposition.solve(Matrix b)

Methods in org.apache.ignite.ml.math.decompositions with parameters of type Matrix

Modifier and Type	Method and Description
protected Matrix	DecompositionSupport.copy(Matrix matrix) Create the copy of matrix with read-only matrices support.
protected Matrix	DecompositionSupport.like(Matrix matrix) Create the like matrix with read-only matrices support.
protected Matrix	DecompositionSupport.like(Matrix matrix, int rows, int cols) Create the like matrix with specified size with read-only matrices support.
protected Vector	DecompositionSupport.likeVector(Matrix matrix) Create the like vector with read-only matrices support.
protected Vector	DecompositionSupport.likeVector(Matrix matrix, int crd) Create the like vector with read-only matrices support.
Matrix	QRDecomposition.solve(Matrix mtx) Least squares solution of A*X = B; returns X.
Matrix	CholeskyDecomposition.solve(Matrix b) Solve the linear equation A × X = B for matrices A.
Matrix	QRDSolver.solve(Matrix mtx) Least squares solution of A*X = B; returns X.
Matrix	LUDecomposition.solve(Matrix b)

Constructors in org.apache.ignite.ml.math.decompositions with parameters of type Matrix

Constructor and Description
CholeskyDecomposition(Matrix mtx) Calculates the Cholesky decomposition of the given matrix.
CholeskyDecomposition(Matrix mtx, double relSymmetryThreshold, double absPositivityThreshold) Calculates the Cholesky decomposition of the given matrix.
EigenDecomposition(Matrix matrix)
EigenDecomposition(Matrix matrix, boolean isSymmetric)
LUDecomposition(Matrix matrix) Calculates the LU-decomposition of the given matrix.
LUDecomposition(Matrix matrix, double singularityThreshold) Calculates the LUP-decomposition of the given matrix.
QRDecomposition(Matrix mtx) Constructs a new QR decomposition object computed by Householder reflections.
QRDecomposition(Matrix mtx, double threshold) Constructs a new QR decomposition object computed by Householder reflections.
QRDSolver(Matrix q, Matrix r) Constructs a new QR decomposition solver object.
SingularValueDecomposition(Matrix arg) Singular value decomposition object.

Uses of Matrix in org.apache.ignite.ml.math.impls.matrix

Classes in org.apache.ignite.ml.math.impls.matrix that implement Matrix

Modifier and Type	Class and Description
class	AbstractMatrix This class provides a helper implementation of the Matrix interface to minimize the effort required to implement it.
class	CacheMatrix<K,V> Matrix based on existing cache and key and value mapping functions.
class	DenseLocalOffHeapMatrix Dense local off-heap implementation of the Matrix interface.
class	DenseLocalOnHeapMatrix Basic implementation for matrix.
class	DiagonalMatrix Implementation of diagonal view of the Matrix.
class	FunctionMatrix Implementation of Matrix that maps row and column index to java.util.function interfaces.
class	MatrixBlockEntry Block for SparseBlockDistributedMatrix.
class	MatrixView Implements the rectangular view into the parent Matrix.
class	PivotedMatrixView Pivoted (index mapped) view over another matrix implementation.
class	RandomMatrix Implementation of Matrix with random values in the elements.
class	SparseBlockDistributedMatrix Sparse block distributed matrix.
class	SparseDistributedMatrix Sparse distributed matrix implementation based on data grid.
class	SparseLocalOnHeapMatrix Sparse local onheap matrix with SparseLocalVector as rows.
class	TransposedMatrixView Implements transposed view of the parent Matrix.

Methods in org.apache.ignite.ml.math.impls.matrix that return Matrix

Modifier and Type	Method and Description
Matrix	AbstractMatrix.assign(double val) Assigns given value to all elements of this matrix.
Matrix	CacheMatrix.assign(double val) Assigns given value to all elements of this matrix.
Matrix	SparseBlockDistributedMatrix.assign(double val) Assigns given value to all elements of this matrix.
Matrix	SparseDistributedMatrix.assign(double val) Assigns given value to all elements of this matrix.
Matrix	AbstractMatrix.assign(double[][] vals) Assigns given values to this matrix.
Matrix	AbstractMatrix.assign(IntIntToDoubleFunction fun) Assigns each matrix element to the value generated by given function.
Matrix	AbstractMatrix.assign(Matrix mtx) Assigns values from given matrix to this matrix.
Matrix	AbstractMatrix.assignColumn(int col, Vector vec) Assigns values from given vector to the specified column in this matrix.
Matrix	AbstractMatrix.assignRow(int row, Vector vec) Assigns values from given vector to the specified row in this matrix.
Matrix	TransposedMatrixView.copy() Clones this matrix.
Matrix	DenseLocalOnHeapMatrix.copy() Clones this matrix.
Matrix	AbstractMatrix.copy() Clones this matrix.
Matrix	FunctionMatrix.copy() Clones this matrix.
Matrix	SparseLocalOnHeapMatrix.copy() Clones this matrix.
Matrix	DenseLocalOffHeapMatrix.copy() Clones this matrix.
Matrix	CacheMatrix.copy() Clones this matrix.
Matrix	SparseBlockDistributedMatrix.copy() Clones this matrix.
Matrix	DiagonalMatrix.copy() Clones this matrix.
Matrix	SparseDistributedMatrix.copy() Clones this matrix.
Matrix	MatrixView.copy() Clones this matrix.
Matrix	PivotedMatrixView.copy() Clones this matrix.
Matrix	RandomMatrix.copy() Clones this matrix.
Matrix	AbstractMatrix.divide(double d) Divides each value in this matrix by the argument.
Matrix	CacheMatrix.divide(double d) Return the same matrix with updates values (broken contract).
Matrix	SparseBlockDistributedMatrix.divide(double d) Return the same matrix with updates values (broken contract).
Matrix	SparseDistributedMatrix.divide(double d) Return the same matrix with updates values (broken contract).
Matrix	PivotedMatrixView.getBaseMatrix()
Matrix	AbstractMatrix.inverse() Returns the inverse matrix of this matrix
Matrix	TransposedMatrixView.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	DenseLocalOnHeapMatrix.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	FunctionMatrix.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	SparseLocalOnHeapMatrix.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	DenseLocalOffHeapMatrix.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	CacheMatrix.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	SparseBlockDistributedMatrix.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	DiagonalMatrix.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	SparseDistributedMatrix.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	MatrixView.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	PivotedMatrixView.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
Matrix	RandomMatrix.like(int rows, int cols) Creates new empty matrix of the same underlying class but of different size.
protected Matrix	AbstractMatrix.likeIdentity()
protected Matrix	DenseLocalOffHeapMatrix.likeIdentity()
Matrix	AbstractMatrix.map(IgniteDoubleFunction<Double> fun) Maps all values in this matrix through a given function.
Matrix	CacheMatrix.map(IgniteDoubleFunction<Double> fun) Maps all values in this matrix through a given function.
Matrix	SparseBlockDistributedMatrix.map(IgniteDoubleFunction<Double> fun) Maps all values in this matrix through a given function.
Matrix	SparseDistributedMatrix.map(IgniteDoubleFunction<Double> fun) Maps all values in this matrix through a given function.
Matrix	AbstractMatrix.map(Matrix mtx, IgniteBiFunction<Double,Double,Double> fun) Maps all values in this matrix through a given function.
Matrix	AbstractMatrix.minus(Matrix mtx) Creates new matrix where each value is a difference between corresponding value of this matrix and passed in argument matrix.
Matrix	AbstractMatrix.plus(double x) Creates new matrix where each value is a sum of the corresponding value of this matrix and argument value.
Matrix	CacheMatrix.plus(double x) Return the same matrix with updates values (broken contract).
Matrix	SparseBlockDistributedMatrix.plus(double x) Return the same matrix with updates values (broken contract).
Matrix	SparseDistributedMatrix.plus(double x) Return the same matrix with updates values (broken contract).
Matrix	AbstractMatrix.plus(Matrix mtx) Creates new matrix where each value is a sum of corresponding values of this matrix and passed in argument matrix.
Matrix	AbstractMatrix.set(int row, int col, double val) Sets given value.
Matrix	AbstractMatrix.setColumn(int col, double[] data) Sets values for given column.
Matrix	AbstractMatrix.setRow(int row, double[] data) Sets values for given row.
Matrix	AbstractMatrix.setX(int row, int col, double val) Sets given value without checking for index bounds.
Matrix	PivotedMatrixView.swap(int i, int j) Swaps indexes i and j for both both row and column.
Matrix	AbstractMatrix.swapColumns(int col1, int col2) Swaps two columns in this matrix.
Matrix	PivotedMatrixView.swapColumns(int i, int j) Swaps two columns in this matrix.
Matrix	AbstractMatrix.swapRows(int row1, int row2) Swaps two rows in this matrix.
Matrix	PivotedMatrixView.swapRows(int i, int j) Swaps two rows in this matrix.
Matrix	AbstractMatrix.times(double x) Creates new matrix containing the product of given value and values in this matrix.
Matrix	CacheMatrix.times(double x) Return the same matrix with updates values (broken contract).
Matrix	SparseBlockDistributedMatrix.times(double x) Return the same matrix with updates values (broken contract).
Matrix	SparseDistributedMatrix.times(double x) Return the same matrix with updates values (broken contract).
Matrix	AbstractMatrix.times(Matrix mtx) Creates new matrix that is the product of multiplying this matrix and the argument matrix.
Matrix	DenseLocalOffHeapMatrix.times(Matrix mtx) TODO: IGNITE-5535, WIP, currently it`s tmp naive impl.
Matrix	SparseBlockDistributedMatrix.times(Matrix mtx) Creates new matrix that is the product of multiplying this matrix and the argument matrix.
Matrix	SparseDistributedMatrix.times(Matrix mtx) Creates new matrix that is the product of multiplying this matrix and the argument matrix.
Matrix	AbstractMatrix.transpose() Creates new matrix that is transpose of this matrix.
Matrix	AbstractMatrix.viewPart(int[] off, int[] size) Creates new view into this matrix.
Matrix	AbstractMatrix.viewPart(int rowOff, int rows, int colOff, int cols) Creates new view into this matrix.

Methods in org.apache.ignite.ml.math.impls.matrix with parameters of type Matrix

Modifier and Type	Method and Description
Matrix	AbstractMatrix.assign(Matrix mtx) Assigns values from given matrix to this matrix.
Matrix	AbstractMatrix.map(Matrix mtx, IgniteBiFunction<Double,Double,Double> fun) Maps all values in this matrix through a given function.
Matrix	AbstractMatrix.minus(Matrix mtx) Creates new matrix where each value is a difference between corresponding value of this matrix and passed in argument matrix.
Matrix	AbstractMatrix.plus(Matrix mtx) Creates new matrix where each value is a sum of corresponding values of this matrix and passed in argument matrix.
Matrix	AbstractMatrix.times(Matrix mtx) Creates new matrix that is the product of multiplying this matrix and the argument matrix.
Matrix	DenseLocalOffHeapMatrix.times(Matrix mtx) TODO: IGNITE-5535, WIP, currently it`s tmp naive impl.
Matrix	SparseBlockDistributedMatrix.times(Matrix mtx) Creates new matrix that is the product of multiplying this matrix and the argument matrix.
Matrix	SparseDistributedMatrix.times(Matrix mtx) Creates new matrix that is the product of multiplying this matrix and the argument matrix.

Constructors in org.apache.ignite.ml.math.impls.matrix with parameters of type Matrix

Constructor and Description
DiagonalMatrix(Matrix mtx)
MatrixBlockEntry(Matrix mtx)
MatrixView(Matrix parent, int rowOff, int colOff, int rows, int cols)
PivotedMatrixView(Matrix mtx)
PivotedMatrixView(Matrix mtx, int[] pivot)
PivotedMatrixView(Matrix mtx, int[] rowPivot, int[] colPivot)
TransposedMatrixView(Matrix mtx)

Uses of Matrix in org.apache.ignite.ml.math.impls.storage.vector

Constructors in org.apache.ignite.ml.math.impls.storage.vector with parameters of type Matrix

Constructor and Description
MatrixVectorStorage(Matrix parent, int row, int col, int rowStride, int colStride)

Uses of Matrix in org.apache.ignite.ml.math.impls.vector

Methods in org.apache.ignite.ml.math.impls.vector that return Matrix

Modifier and Type	Method and Description
Matrix	AbstractVector.cross(Vector vec) Gets the cross product of this vector and the other vector.
Matrix	AbstractReadOnlyVector.cross(Vector vec) Gets the cross product of this vector and the other vector.
Matrix	DelegatingVector.cross(Vector vec) Gets the cross product of this vector and the other vector.
Matrix	PivotedVectorView.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	SparseBlockDistributedVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	MatrixVectorView.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	SparseDistributedVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	DenseLocalOffHeapVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	SparseLocalVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	SingleElementVectorView.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	SingleElementVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	SparseLocalOffHeapVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	VectorView.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	CacheVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	MapWrapperVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	FunctionVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	DelegatingVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	ConstantVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	DenseLocalOnHeapVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	RandomVector.likeMatrix(int rows, int cols) Creates new matrix of compatible flavor with given size.
Matrix	AbstractVector.toMatrix(boolean rowLike) Converts this vector into [N x 1] or [1 x N] matrix where N is this vector cardinality.
Matrix	AbstractReadOnlyVector.toMatrix(boolean rowLike) Converts this vector into [N x 1] or [1 x N] matrix where N is this vector cardinality.
Matrix	DelegatingVector.toMatrix(boolean rowLike) Converts this vector into [N x 1] or [1 x N] matrix where N is this vector cardinality.
Matrix	AbstractVector.toMatrixPlusOne(boolean rowLike, double zeroVal) Converts this vector into [N+1 x 1] or [1 x N+1] matrix where N is this vector cardinality
Matrix	AbstractReadOnlyVector.toMatrixPlusOne(boolean rowLike, double zeroVal) Converts this vector into [N+1 x 1] or [1 x N+1] matrix where N is this vector cardinality
Matrix	DelegatingVector.toMatrixPlusOne(boolean rowLike, double zeroVal) Converts this vector into [N+1 x 1] or [1 x N+1] matrix where N is this vector cardinality

Constructors in org.apache.ignite.ml.math.impls.vector with parameters of type Matrix

Constructor and Description
MatrixVectorView(Matrix parent, int row, int col, int rowStride, int colStride)

Uses of Matrix in org.apache.ignite.ml.math.util

Methods in org.apache.ignite.ml.math.util that return Matrix

Modifier and Type	Method and Description
static Matrix	MatrixUtil.copy(Matrix matrix) Create the copy of matrix with read-only matrices support.
static Matrix	MatrixUtil.elementWiseMinus(Matrix mtx1, Matrix mtx2) Performs in-place matrix subtraction.
static Matrix	MatrixUtil.elementWiseTimes(Matrix mtx1, Matrix mtx2) Performs in-place matrix multiplication.
static Matrix	MatrixUtil.identityLike(Matrix matrix, int n) Create the identity matrix like a given matrix.
static Matrix	MatrixUtil.like(Matrix matrix) Create the like matrix with read-only matrices support.
static Matrix	MatrixUtil.like(Matrix matrix, int rows, int cols) Create the like matrix with specified size with read-only matrices support.

Methods in org.apache.ignite.ml.math.util with parameters of type Matrix

Modifier and Type	Method and Description
static Matrix	MatrixUtil.copy(Matrix matrix) Create the copy of matrix with read-only matrices support.
static Matrix	MatrixUtil.elementWiseMinus(Matrix mtx1, Matrix mtx2) Performs in-place matrix subtraction.
static Matrix	MatrixUtil.elementWiseTimes(Matrix mtx1, Matrix mtx2) Performs in-place matrix multiplication.
static Matrix	MatrixUtil.identityLike(Matrix matrix, int n) Create the identity matrix like a given matrix.
static Matrix	MatrixUtil.like(Matrix matrix) Create the like matrix with read-only matrices support.
static Matrix	MatrixUtil.like(Matrix matrix, int rows, int cols) Create the like matrix with specified size with read-only matrices support.
static Vector	MatrixUtil.likeVector(Matrix matrix) Create the like vector with read-only matrices support.
static Vector	MatrixUtil.likeVector(Matrix matrix, int crd) Create the like vector with read-only matrices support.
static void	MatrixUtil.unflatten(double[] fArr, Matrix mtx)
static Vector	MatrixUtil.zipFoldByColumns(Matrix mtx1, Matrix mtx2, IgniteBiFunction<Vector,Vector,Double> fun) Zips two matrices by column-by-column with specified function.
static Vector	MatrixUtil.zipFoldByRows(Matrix mtx1, Matrix mtx2, IgniteBiFunction<Vector,Vector,Double> fun) Zips two matrices by row-by-row with specified function.

Uses of Matrix in org.apache.ignite.ml.nn

Fields in org.apache.ignite.ml.nn declared as Matrix

Modifier and Type	Field and Description
protected Matrix	MLPState.input Input.
protected Matrix	MLPLayer.weights Weights matrix.

Fields in org.apache.ignite.ml.nn with type parameters of type Matrix

Modifier and Type	Field and Description
protected List<Matrix>	MLPState.activatorsOutput Output of activators.
protected List<Matrix>	MLPState.linearOutput Output of linear transformations.

Methods in org.apache.ignite.ml.nn that return Matrix

Modifier and Type	Method and Description
Matrix	MLPState.activatorsOutput(int layer) Output of activators of given layer.
Matrix	MultilayerPerceptron.apply(Matrix val) Makes a prediction for the given objects.
Matrix	MultilayerPerceptron.forwardPass(Matrix val, MLPState state, boolean writeState) Perform forward pass and if needed write state of outputs of each layer.
Matrix	MLPState.linearOutput(int layer) Output of linear transformation of given layer.
Matrix	MultilayerPerceptron.weights(int layerIdx) Get weights of layer with given index.

Methods in org.apache.ignite.ml.nn with parameters of type Matrix

Modifier and Type	Method and Description
Matrix	MultilayerPerceptron.apply(Matrix val) Makes a prediction for the given objects.
MLPState	MultilayerPerceptron.computeState(Matrix val) Perform forward pass and return state of outputs of each layer.
Vector	MultilayerPerceptron.differentiateByParameters(IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss, Matrix inputsBatch, Matrix truthBatch) Compose function in the following way: feed output of this model as input to second argument to loss function.
Matrix	MultilayerPerceptron.forwardPass(Matrix val, MLPState state, boolean writeState) Perform forward pass and if needed write state of outputs of each layer.
MultilayerPerceptron	MultilayerPerceptron.setWeights(int layerIdx, Matrix weights) Sets the weighs of layer with a given index.

Constructors in org.apache.ignite.ml.nn with parameters of type Matrix

Constructor and Description
MLPLayer(Matrix weights, Vector biases) Construct MLPLayer from weights and biases.
MLPState(Matrix input) Construct MLP state.

Uses of Matrix in org.apache.ignite.ml.nn.initializers

Methods in org.apache.ignite.ml.nn.initializers with parameters of type Matrix

Modifier and Type	Method and Description
void	RandomInitializer.initWeights(Matrix weights) In-place change values of matrix representing weights.
void	MLPInitializer.initWeights(Matrix weights) In-place change values of matrix representing weights.

Uses of Matrix in org.apache.ignite.ml.optimization

Methods in org.apache.ignite.ml.optimization with parameters of type Matrix

Modifier and Type	Method and Description
Vector	SmoothParametrized.differentiateByParameters(IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss, Matrix inputsBatch, Matrix truthBatch) Compose function in the following way: feed output of this model as input to second argument to loss function.

Uses of Matrix in org.apache.ignite.ml.optimization.updatecalculators

Methods in org.apache.ignite.ml.optimization.updatecalculators with parameters of type Matrix

Modifier and Type	Method and Description
NesterovParameterUpdate	NesterovUpdateCalculator.calculateNewUpdate(M mdl, NesterovParameterUpdate updaterParameters, int iteration, Matrix inputs, Matrix groundTruth) Calculate new update.
P	ParameterUpdateCalculator.calculateNewUpdate(M mdl, P updaterParameters, int iteration, Matrix inputs, Matrix groundTruth) Calculate new update.
RPropParameterUpdate	RPropUpdateCalculator.calculateNewUpdate(SmoothParametrized mdl, RPropParameterUpdate updaterParams, int iteration, Matrix inputs, Matrix groundTruth) Calculate new update.
SimpleGDParameterUpdate	SimpleGDUpdateCalculator.calculateNewUpdate(SmoothParametrized mlp, SimpleGDParameterUpdate updaterParameters, int iteration, Matrix inputs, Matrix groundTruth) Calculate new update.