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Packages that use Matrix | |
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org.apache.mahout.math | Core base classes; Operations on primitive arrays such as sorting, partitioning and permuting. |
org.apache.mahout.math.decomposer.hebbian | |
org.apache.mahout.math.decomposer.lanczos |
Uses of Matrix in org.apache.mahout.math |
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Classes in org.apache.mahout.math that implement Matrix | |
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class |
AbstractMatrix
A few universal implementations of convenience functions |
class |
DenseMatrix
Matrix of doubles implemented using a 2-d array |
class |
MatrixView
Implements subset view of a Matrix |
class |
SparseColumnMatrix
sparse matrix with general element values whose columns are accessible quickly. |
class |
SparseMatrix
Doubly sparse matrix. |
class |
SparseRowMatrix
sparse matrix with general element values whose rows are accessible quickly. |
class |
VectorList
Provides a very flexible matrix that is based on a simple list of vectors. |
Methods in org.apache.mahout.math that return Matrix | |
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Matrix |
Matrix.assign(double value)
Assign the value to all elements of the receiver |
Matrix |
DenseMatrix.assign(double value)
|
Matrix |
AbstractMatrix.assign(double value)
|
Matrix |
Matrix.assign(double[][] values)
Assign the values to the receiver |
Matrix |
AbstractMatrix.assign(double[][] values)
|
Matrix |
Matrix.assign(Matrix other)
Assign the other vector values to the receiver |
Matrix |
AbstractMatrix.assign(Matrix other)
|
Matrix |
Matrix.assign(Matrix other,
BinaryFunction function)
Apply the function to each element of the receiver and the corresponding element of the other argument |
Matrix |
AbstractMatrix.assign(Matrix other,
BinaryFunction function)
|
Matrix |
Matrix.assign(UnaryFunction function)
Apply the function to each element of the receiver |
Matrix |
AbstractMatrix.assign(UnaryFunction function)
|
Matrix |
VectorList.assignColumn(int column,
Vector other)
|
Matrix |
SparseRowMatrix.assignColumn(int column,
Vector other)
|
Matrix |
SparseMatrix.assignColumn(int column,
Vector other)
|
Matrix |
SparseColumnMatrix.assignColumn(int column,
Vector other)
|
Matrix |
MatrixView.assignColumn(int column,
Vector other)
|
Matrix |
Matrix.assignColumn(int column,
Vector other)
Assign the other vector values to the column of the receiver |
Matrix |
DenseMatrix.assignColumn(int column,
Vector other)
|
Matrix |
VectorList.assignRow(int row,
Vector other)
|
Matrix |
SparseRowMatrix.assignRow(int row,
Vector other)
|
Matrix |
SparseMatrix.assignRow(int row,
Vector other)
|
Matrix |
SparseColumnMatrix.assignRow(int row,
Vector other)
|
Matrix |
MatrixView.assignRow(int row,
Vector other)
|
Matrix |
Matrix.assignRow(int row,
Vector other)
Assign the other vector values to the row of the receiver |
Matrix |
DenseMatrix.assignRow(int row,
Vector other)
|
Matrix |
SparseRowMatrix.clone()
|
Matrix |
SparseMatrix.clone()
|
Matrix |
SparseColumnMatrix.clone()
|
Matrix |
MatrixView.clone()
|
Matrix |
Matrix.clone()
Return a copy of the recipient |
Matrix |
DenseMatrix.clone()
|
Matrix |
AbstractMatrix.clone()
|
Matrix |
Vector.cross(Vector other)
Return the cross product of the receiver and the other vector |
Matrix |
NamedVector.cross(Vector other)
|
Matrix |
AbstractVector.cross(Vector other)
|
static Matrix |
AbstractMatrix.decodeMatrix(java.lang.String formatString)
|
Matrix |
JsonMatrixAdapter.deserialize(com.google.gson.JsonElement json,
java.lang.reflect.Type typeOfT,
com.google.gson.JsonDeserializationContext context)
|
Matrix |
Matrix.divide(double x)
Return a new matrix containing the values of the recipient divided by the argument |
Matrix |
AbstractMatrix.divide(double x)
|
Matrix |
QRDecomposition.getH()
Deprecated. |
Matrix |
QRDecomposition.getQ()
Generates and returns the (economy-sized) orthogonal factor Q. |
Matrix |
QRDecomposition.getR()
Returns the upper triangular factor, R. |
Matrix |
SingularValueDecomposition.getS()
|
Matrix |
SingularValueDecomposition.getU()
Returns the left singular vectors U. |
Matrix |
SingularValueDecomposition.getV()
Returns the right singular vectors V. |
Matrix |
VectorList.like()
Return an empty matrix of the same underlying class as the receiver |
Matrix |
SparseRowMatrix.like()
|
Matrix |
SparseMatrix.like()
|
Matrix |
SparseColumnMatrix.like()
|
Matrix |
MatrixView.like()
|
Matrix |
Matrix.like()
Return an empty matrix of the same underlying class as the receiver |
Matrix |
DenseMatrix.like()
|
Matrix |
VectorList.like(int rows,
int columns)
Returns an empty matrix of the same underlying class as the receiver and of the specified size. |
Matrix |
SparseRowMatrix.like(int rows,
int columns)
|
Matrix |
SparseMatrix.like(int rows,
int columns)
|
Matrix |
SparseColumnMatrix.like(int rows,
int columns)
|
Matrix |
MatrixView.like(int rows,
int columns)
|
Matrix |
Matrix.like(int rows,
int columns)
Returns an empty matrix of the same underlying class as the receiver and of the specified size. |
Matrix |
DenseMatrix.like(int rows,
int columns)
|
protected Matrix |
VectorView.matrixLike(int rows,
int columns)
|
protected Matrix |
SequentialAccessSparseVector.matrixLike(int rows,
int columns)
|
protected Matrix |
RandomAccessSparseVector.matrixLike(int rows,
int columns)
|
protected Matrix |
MatrixVectorView.matrixLike(int rows,
int columns)
Subclasses must override to return an appropriately sparse or dense result |
protected Matrix |
DenseVector.matrixLike(int rows,
int columns)
|
protected abstract Matrix |
AbstractVector.matrixLike(int rows,
int columns)
Subclasses must override to return an appropriately sparse or dense result |
protected Matrix |
AbstractMatrix.TransposeViewVector.matrixLike(int rows,
int columns)
|
Matrix |
Matrix.minus(Matrix x)
Return a new matrix containing the element by element difference of the recipient and the argument |
Matrix |
AbstractMatrix.minus(Matrix other)
|
Matrix |
Matrix.plus(double x)
Return a new matrix containing the sum of each value of the recipient and the argument |
Matrix |
AbstractMatrix.plus(double x)
|
Matrix |
Matrix.plus(Matrix x)
Return a new matrix containing the element by element sum of the recipient and the argument |
Matrix |
AbstractMatrix.plus(Matrix other)
|
Matrix |
QRDecomposition.solve(Matrix B)
Least squares solution of A*X = B; returns X. |
Matrix |
Matrix.times(double x)
Return a new matrix containing the product of each value of the recipient and the argument |
Matrix |
AbstractMatrix.times(double x)
|
Matrix |
Matrix.times(Matrix x)
Return a new matrix containing the product of the recipient and the argument |
Matrix |
AbstractMatrix.times(Matrix other)
|
Matrix |
Matrix.transpose()
Return a new matrix that is the transpose of the receiver |
Matrix |
AbstractMatrix.transpose()
|
Matrix |
VectorList.viewPart(int[] offset,
int[] size)
Return a new matrix containing the subset of the recipient |
Matrix |
SparseRowMatrix.viewPart(int[] offset,
int[] size)
|
Matrix |
SparseMatrix.viewPart(int[] offset,
int[] size)
|
Matrix |
SparseColumnMatrix.viewPart(int[] offset,
int[] size)
|
Matrix |
MatrixView.viewPart(int[] offset,
int[] size)
|
Matrix |
Matrix.viewPart(int[] offset,
int[] size)
Return a new matrix containing the subset of the recipient |
Matrix |
DenseMatrix.viewPart(int[] offset,
int[] size)
|
Matrix |
Matrix.viewPart(int rowOffset,
int rowsRequested,
int columnOffset,
int columnsRequested)
Return a new matrix containing the subset of the recipient |
Matrix |
DenseMatrix.viewPart(int rowOffset,
int rowsRequested,
int columnOffset,
int columnsRequested)
|
Matrix |
AbstractMatrix.viewPart(int rowOffset,
int rowsRequested,
int columnOffset,
int columnsRequested)
|
Methods in org.apache.mahout.math with parameters of type Matrix | |
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void |
VectorList.adjoinRow(Matrix other)
|
Matrix |
Matrix.assign(Matrix other)
Assign the other vector values to the receiver |
Matrix |
AbstractMatrix.assign(Matrix other)
|
Matrix |
Matrix.assign(Matrix other,
BinaryFunction function)
Apply the function to each element of the receiver and the corresponding element of the other argument |
Matrix |
AbstractMatrix.assign(Matrix other,
BinaryFunction function)
|
static double |
Algebra.getNorm(Matrix m)
Compute Maximum Absolute Row Sum Norm of input Matrix m http://mathworld.wolfram.com/MaximumAbsoluteRowSumNorm.html |
Matrix |
Matrix.minus(Matrix x)
Return a new matrix containing the element by element difference of the recipient and the argument |
Matrix |
AbstractMatrix.minus(Matrix other)
|
static Vector |
Algebra.mult(Matrix m,
Vector v)
|
Matrix |
Matrix.plus(Matrix x)
Return a new matrix containing the element by element sum of the recipient and the argument |
Matrix |
AbstractMatrix.plus(Matrix other)
|
com.google.gson.JsonElement |
JsonMatrixAdapter.serialize(Matrix src,
java.lang.reflect.Type typeOfSrc,
com.google.gson.JsonSerializationContext context)
|
Matrix |
QRDecomposition.solve(Matrix B)
Least squares solution of A*X = B; returns X. |
Matrix |
Matrix.times(Matrix x)
Return a new matrix containing the product of the recipient and the argument |
Matrix |
AbstractMatrix.times(Matrix other)
|
Constructors in org.apache.mahout.math with parameters of type Matrix | |
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AbstractMatrix.TransposeViewVector(Matrix m,
int offset)
|
|
AbstractMatrix.TransposeViewVector(Matrix m,
int offset,
boolean rowToColumn)
|
|
MatrixVectorView(Matrix matrix,
int row,
int column,
int rowStride,
int columnStride)
|
|
MatrixView(Matrix matrix,
int[] offset,
int[] size)
Construct a view of the matrix with given offset and cardinality |
|
QRDecomposition(Matrix a)
Constructs and returns a new QR decomposition object; computed by Householder reflections; The decomposed matrices can be retrieved via instance methods of the returned decomposition object. |
|
SingularValueDecomposition(Matrix arg)
Constructs and returns a new singular value decomposition object; The decomposed matrices can be retrieved via instance methods of the returned decomposition object. |
Uses of Matrix in org.apache.mahout.math.decomposer.hebbian |
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Methods in org.apache.mahout.math.decomposer.hebbian that return Matrix | |
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Matrix |
TrainingState.getCurrentEigens()
|
Matrix |
TrainingState.getTrainingProjections()
|
Methods in org.apache.mahout.math.decomposer.hebbian with parameters of type Matrix | |
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protected boolean |
HebbianSolver.hasNotConverged(Vector currentPseudoEigen,
Matrix corpus,
TrainingState state)
Uses the SingularVectorVerifier to check for convergence |
void |
TrainingState.setCurrentEigens(Matrix currentEigens)
|
void |
TrainingState.setTrainingProjections(Matrix trainingProjections)
|
TrainingState |
HebbianSolver.solve(Matrix corpus,
int desiredRank)
Primary singular vector solving method. |
protected EigenStatus |
HebbianSolver.verify(Matrix corpus,
Vector currentPseudoEigen)
|
Uses of Matrix in org.apache.mahout.math.decomposer.lanczos |
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Methods in org.apache.mahout.math.decomposer.lanczos with parameters of type Matrix | |
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void |
LanczosSolver.solve(VectorIterable corpus,
int desiredRank,
Matrix eigenVectors,
java.util.List<java.lang.Double> eigenValues)
|
void |
LanczosSolver.solve(VectorIterable corpus,
int desiredRank,
Matrix eigenVectors,
java.util.List<java.lang.Double> eigenValues,
boolean isSymmetric)
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