Uses of Interface
org.apache.mahout.math.Matrix

Packages that use Matrix
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
 

Classes in org.apache.mahout.math that implement Matrix
 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
 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
 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
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
 

Methods in org.apache.mahout.math.decomposer.hebbian that return Matrix
 Matrix TrainingState.getCurrentEigens()
           
 Matrix TrainingState.getTrainingProjections()
           
 

Methods in org.apache.mahout.math.decomposer.hebbian with parameters of type Matrix
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
 

Methods in org.apache.mahout.math.decomposer.lanczos with parameters of type Matrix
 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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