Package | Description |
---|---|
org.apache.ignite.ml.composition.stacking |
Contains classes used for training with stacking technique.
|
org.apache.ignite.ml.math |
Contains main APIs for matrix/vector algebra.
|
org.apache.ignite.ml.math.primitives.matrix |
Contains matrix related classes.
|
org.apache.ignite.ml.math.primitives.matrix.impl |
Contains several matrix implementations.
|
org.apache.ignite.ml.math.primitives.vector |
Contains vector related classes.
|
org.apache.ignite.ml.math.primitives.vector.impl |
Contains several vector implementations.
|
org.apache.ignite.ml.math.primitives.vector.storage |
Contains several vector storages.
|
org.apache.ignite.ml.math.stat |
Contains utility classes for distributions.
|
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.
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org.apache.ignite.ml.optimization.updatecalculators |
Contains update calculators.
|
Modifier and Type | Method and Description |
---|---|
<M1 extends IgniteModel<Matrix,Matrix>> |
StackedVectorDatasetTrainer.addMatrix2MatrixTrainer(DatasetTrainer<M1,L> trainer)
|
<M1 extends IgniteModel<Matrix,Matrix>> |
StackedVectorDatasetTrainer.addMatrix2MatrixTrainer(DatasetTrainer<M1,L> trainer)
|
Modifier and Type | Method and Description |
---|---|
static String |
Tracer.asAscii(Matrix mtx,
String fmt) |
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.
|
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.
|
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. |
Modifier and Type | Method and Description |
---|---|
Matrix |
AbstractMatrix.assign(double val)
Assigns given value to all elements of this matrix.
|
Matrix |
Matrix.assign(double val)
Assigns given value to all elements of this matrix.
|
Matrix |
AbstractMatrix.assign(double[][] vals)
Assigns given values to this matrix.
|
Matrix |
Matrix.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 |
Matrix.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 |
Matrix.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 |
Matrix.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 |
Matrix.assignRow(int row,
Vector vec)
Assigns values from given vector to the specified row in this matrix.
|
Matrix |
AbstractMatrix.copy()
Clones this matrix.
|
Matrix |
Matrix.copy()
Clones this matrix.
|
Matrix |
AbstractMatrix.divide(double d)
Divides each value in this matrix by the argument.
|
Matrix |
Matrix.divide(double x)
Divides each value in this matrix by the argument.
|
Matrix |
LUDecomposition.getL()
Returns the matrix L of the decomposition.
|
Matrix |
LUDecomposition.getP()
Returns the P rows permutation matrix.
|
Matrix |
LUDecomposition.getU()
Returns the matrix U of the decomposition.
|
Matrix |
AbstractMatrix.inverse()
Returns the inverse matrix of this matrix
|
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.
|
protected Matrix |
AbstractMatrix.likeIdentity() |
Matrix |
AbstractMatrix.map(IgniteDoubleFunction<Double> fun)
Maps all values in this matrix through a given function.
|
Matrix |
Matrix.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 |
Matrix.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 |
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 |
AbstractMatrix.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(double x)
Creates new matrix where each value is a sum of the corresponding value of this matrix and
argument value.
|
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 |
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 |
AbstractMatrix.set(int row,
int col,
double val)
Sets given value.
|
Matrix |
Matrix.set(int row,
int col,
double val)
Sets given value.
|
Matrix |
AbstractMatrix.setColumn(int col,
double[] data)
Sets values for given column.
|
Matrix |
Matrix.setColumn(int col,
double[] data)
Sets values for given column.
|
Matrix |
AbstractMatrix.setRow(int row,
double[] data)
Sets values for given row.
|
Matrix |
Matrix.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 |
Matrix.setX(int row,
int col,
double val)
Sets given value without checking for index bounds.
|
Matrix |
LUDecomposition.solve(Matrix b) |
Matrix |
AbstractMatrix.swapColumns(int col1,
int col2)
Swaps two columns in this matrix.
|
Matrix |
Matrix.swapColumns(int col1,
int col2)
Swaps two columns in this matrix.
|
Matrix |
AbstractMatrix.swapRows(int row1,
int row2)
Swaps two rows in this matrix.
|
Matrix |
Matrix.swapRows(int row1,
int row2)
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 |
Matrix.times(double x)
Creates new matrix containing the product of given value and values in this matrix.
|
Matrix |
AbstractMatrix.times(Matrix mtx)
Creates new matrix that is the product of multiplying this matrix and the argument matrix.
|
Matrix |
Matrix.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 |
Matrix.transpose()
Creates new matrix that is transpose of this matrix.
|
Modifier and Type | Method and Description |
---|---|
Matrix |
AbstractMatrix.assign(Matrix mtx)
Assigns values from given matrix to this matrix.
|
Matrix |
Matrix.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 |
Matrix.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 |
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 |
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 |
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 |
LUDecomposition.solve(Matrix b) |
Matrix |
AbstractMatrix.times(Matrix mtx)
Creates new matrix that is the product of multiplying this matrix and the argument matrix.
|
Matrix |
Matrix.times(Matrix mtx)
Creates new matrix that is the product of multiplying this matrix and the argument matrix.
|
Constructor and Description |
---|
LUDecomposition(Matrix matrix)
Calculates the LU-decomposition of the given matrix.
|
LUDecomposition(Matrix matrix,
double singularityThreshold)
Calculates the LUP-decomposition of the given matrix.
|
Modifier and Type | Class and Description |
---|---|
class |
DenseMatrix
Basic implementation for matrix.
|
class |
SparseMatrix
Sparse local onheap matrix with
SparseVector as rows. |
class |
ViewMatrix
Implements the rectangular view into the parent
Matrix . |
Modifier and Type | Method and Description |
---|---|
Matrix |
SparseMatrix.copy()
Clones this matrix.
|
Matrix |
DenseMatrix.copy()
Clones this matrix.
|
Matrix |
ViewMatrix.copy()
Clones this matrix.
|
Matrix |
SparseMatrix.like(int rows,
int cols)
Creates new empty matrix of the same underlying class but of different size.
|
Matrix |
DenseMatrix.like(int rows,
int cols)
Creates new empty matrix of the same underlying class but of different size.
|
Matrix |
ViewMatrix.like(int rows,
int cols)
Creates new empty matrix of the same underlying class but of different size.
|
Constructor and Description |
---|
ViewMatrix(Matrix parent,
int rowOff,
int colOff,
int rows,
int cols) |
Modifier and Type | Method and Description |
---|---|
Matrix |
Vector.cross(Vector vec)
Gets the cross product of this vector and the other vector.
|
Matrix |
AbstractVector.cross(Vector vec)
Gets the cross product of this vector and the other vector.
|
Matrix |
Vector.likeMatrix(int rows,
int cols)
Creates new matrix of compatible flavor with given size.
|
Matrix |
Vector.toMatrix(boolean rowLike)
Converts this vector into [N x 1] or [1 x N] matrix where N is this vector cardinality.
|
Matrix |
AbstractVector.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 |
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
|
Modifier and Type | Method and Description |
---|---|
Matrix |
DelegatingVector.cross(Vector vec)
Gets the cross product of this vector and the other vector.
|
Matrix |
DelegatingVector.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 |
VectorizedViewMatrix.likeMatrix(int rows,
int cols)
Creates new matrix of compatible flavor with given size.
|
Matrix |
SparseVector.likeMatrix(int rows,
int cols)
Creates new matrix of compatible flavor with given size.
|
Matrix |
DenseVector.likeMatrix(int rows,
int cols)
Creates new matrix of compatible flavor with given size.
|
Matrix |
DelegatingVector.toMatrix(boolean rowLike)
Converts this vector into [N x 1] or [1 x N] 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
|
Constructor and Description |
---|
VectorizedViewMatrix(Matrix parent,
int row,
int col,
int rowStride,
int colStride) |
Constructor and Description |
---|
VectorizedViewMatrixStorage(Matrix parent,
int row,
int col,
int rowStride,
int colStride) |
Modifier and Type | Method and Description |
---|---|
Matrix |
MultivariateGaussianDistribution.covariance() |
Constructor and Description |
---|
MultivariateGaussianDistribution(Vector mean,
Matrix covariance)
Constructs an instance of MultivariateGaussianDistribution.
|
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.identity(int n) |
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.
|
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.
|
Modifier and Type | Field and Description |
---|---|
protected Matrix |
MLPState.input
Input.
|
protected Matrix |
MLPLayer.weights
Weights matrix.
|
Modifier and Type | Field and Description |
---|---|
protected List<Matrix> |
MLPState.activatorsOutput
Output of activators.
|
protected List<Matrix> |
MLPState.linearOutput
Output of linear transformations.
|
Modifier and Type | Method and Description |
---|---|
Matrix |
MLPState.activatorsOutput(int layer)
Output of activators of given layer.
|
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.predict(Matrix val)
Makes a prediction for the given objects.
|
Matrix |
MultilayerPerceptron.weights(int layerIdx)
Get weights of layer with given index.
|
Modifier and Type | Method and Description |
---|---|
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.
|
Matrix |
MultilayerPerceptron.predict(Matrix val)
Makes a prediction for the given objects.
|
MultilayerPerceptron |
MultilayerPerceptron.setWeights(int layerIdx,
Matrix weights)
Sets the weighs of layer with a given index.
|
Constructor and Description |
---|
MLPLayer(Matrix weights,
Vector biases)
Construct MLPLayer from weights and biases.
|
MLPState(Matrix input)
Construct MLP state.
|
Modifier and Type | Method and Description |
---|---|
void |
MLPInitializer.initWeights(Matrix weights)
In-place change values of matrix representing weights.
|
void |
RandomInitializer.initWeights(Matrix weights)
In-place change values of matrix representing weights.
|
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.
|
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.
|
GridGain In-Memory Computing Platform : ver. 8.9.14 Release Date : November 5 2024