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Packages that use Vector | |
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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.als | |
org.apache.mahout.math.decomposer | |
org.apache.mahout.math.decomposer.hebbian | |
org.apache.mahout.math.decomposer.lanczos | |
org.apache.mahout.math.function | Core interfaces for functions, comparisons and procedures on objects and primitive data types. |
org.apache.mahout.math.matrix | |
org.apache.mahout.math.matrix.impl | Matrix implementations; You normally need not look at this package, because all concrete classes implement the
abstract interfaces of org.apache.mahout.math.matrix , without subsetting or supersetting. |
org.apache.mahout.math.solver | |
org.apache.mahout.math.ssvd |
Uses of Vector in org.apache.mahout.math |
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Classes in org.apache.mahout.math that implement Vector | |
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protected class |
AbstractMatrix.TransposeViewVector
|
class |
AbstractVector
Implementations of generic capabilities like sum of elements and dot products |
class |
ConstantVector
Implements a vector with all the same values. |
class |
DenseVector
Implements vector as an array of doubles |
class |
MatrixVectorView
Provides a virtual vector that is really a row or column or diagonal of a matrix. |
class |
NamedVector
|
class |
PermutedVectorView
Provides a permuted view of a vector. |
class |
RandomAccessSparseVector
Implements vector that only stores non-zero doubles |
class |
SequentialAccessSparseVector
Implements vector that only stores non-zero doubles as a pair of parallel arrays (OrderedIntDoubleMapping), one int[], one double[]. |
class |
VectorView
Implements subset view of a Vector |
Methods in org.apache.mahout.math that return Vector | |
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Vector |
Matrix.aggregateColumns(VectorFunction f)
Collects the results of a function applied to each column of a matrix. |
Vector |
AbstractMatrix.aggregateColumns(VectorFunction f)
Collects the results of a function applied to each column of a matrix. |
Vector |
Matrix.aggregateRows(VectorFunction f)
Collects the results of a function applied to each row of a matrix. |
Vector |
AbstractMatrix.aggregateRows(VectorFunction f)
Collects the results of a function applied to each row of a matrix. |
Vector |
DenseVector.assign(DenseVector vector)
|
Vector |
Vector.assign(double value)
Assign the value to all elements of the receiver |
Vector |
NamedVector.assign(double value)
|
Vector |
DenseVector.assign(double value)
|
Vector |
AbstractVector.assign(double value)
|
Vector |
Vector.assign(double[] values)
Assign the values to the receiver |
Vector |
NamedVector.assign(double[] values)
|
Vector |
AbstractVector.assign(double[] values)
|
Vector |
Vector.assign(DoubleDoubleFunction f,
double y)
Apply the function to each element of the receiver, using the y value as the second argument of the DoubleDoubleFunction |
Vector |
NamedVector.assign(DoubleDoubleFunction f,
double y)
|
Vector |
AbstractVector.assign(DoubleDoubleFunction f,
double y)
|
Vector |
Vector.assign(DoubleFunction function)
Apply the function to each element of the receiver |
Vector |
NamedVector.assign(DoubleFunction function)
|
Vector |
AbstractVector.assign(DoubleFunction function)
|
Vector |
Vector.assign(Vector other)
Assign the other vector values to the receiver |
Vector |
SequentialAccessSparseVector.assign(Vector other)
|
Vector |
RandomAccessSparseVector.assign(Vector other)
|
Vector |
NamedVector.assign(Vector other)
|
Vector |
AbstractVector.assign(Vector other)
|
Vector |
Vector.assign(Vector other,
DoubleDoubleFunction function)
Apply the function to each element of the receiver and the corresponding element of the other argument |
Vector |
NamedVector.assign(Vector other,
DoubleDoubleFunction function)
|
Vector |
DenseVector.assign(Vector other,
DoubleDoubleFunction function)
|
Vector |
AbstractVector.assign(Vector other,
DoubleDoubleFunction function)
|
Vector |
VectorView.clone()
|
Vector |
Vector.clone()
Return a copy of the recipient |
Vector |
MatrixVectorView.clone()
|
Vector |
AbstractVector.clone()
|
Vector |
AbstractMatrix.TransposeViewVector.clone()
|
Vector |
Vector.divide(double x)
Return a new vector containing the values of the recipient divided by the argument |
Vector |
NamedVector.divide(double x)
|
Vector |
AbstractVector.divide(double x)
|
Vector |
NamedVector.getDelegate()
|
Vector |
Vector.like()
Return an empty vector of the same underlying class as the receiver |
Vector |
PermutedVectorView.like()
Return an empty vector of the same underlying class as the receiver |
Vector |
MatrixVectorView.like()
Return an empty vector of the same underlying class as the receiver |
Vector |
ConstantVector.like()
Return an empty vector of the same underlying class as the receiver |
Vector |
AbstractMatrix.TransposeViewVector.like()
|
Vector |
AbstractMatrix.TransposeViewVector.like(int cardinality)
|
Vector |
Vector.logNormalize()
Return a new vector containing the log(1 + entry)/ L_2 norm values of the recipient |
Vector |
NamedVector.logNormalize()
|
Vector |
AbstractVector.logNormalize()
|
Vector |
Vector.logNormalize(double power)
Return a new Vector with a normalized value calculated as log_power(1 + entry)/ L_power norm. |
Vector |
NamedVector.logNormalize(double power)
|
Vector |
AbstractVector.logNormalize(double power)
|
Vector |
AbstractVector.logNormalize(double power,
double normLength)
|
Vector |
Vector.minus(Vector x)
Return a new vector containing the element by element difference of the recipient and the argument |
Vector |
SequentialAccessSparseVector.minus(Vector that)
|
Vector |
NamedVector.minus(Vector x)
|
Vector |
AbstractVector.minus(Vector that)
|
static Vector |
Algebra.mult(Matrix m,
Vector v)
|
protected Vector |
AbstractMatrix.TransposeViewVector.newVector(int cardinality)
|
Vector |
Vector.normalize()
Return a new vector containing the normalized (L_2 norm) values of the recipient |
Vector |
NamedVector.normalize()
|
Vector |
AbstractVector.normalize()
|
Vector |
Vector.normalize(double power)
Return a new Vector containing the normalized (L_power norm) values of the recipient. |
Vector |
NamedVector.normalize(double power)
|
Vector |
AbstractVector.normalize(double power)
|
Vector |
Vector.plus(double x)
Return a new vector containing the sum of each value of the recipient and the argument |
Vector |
NamedVector.plus(double x)
|
Vector |
AbstractVector.plus(double x)
|
Vector |
Vector.plus(Vector x)
Return a new vector containing the element by element sum of the recipient and the argument |
Vector |
NamedVector.plus(Vector x)
|
Vector |
AbstractVector.plus(Vector x)
|
Vector |
Vector.times(double x)
Return a new vector containing the product of each value of the recipient and the argument |
Vector |
NamedVector.times(double x)
|
Vector |
AbstractVector.times(double x)
|
Vector |
VectorIterable.times(Vector v)
Return a new vector with cardinality equal to getNumRows() of this matrix which is the matrix product of the recipient and the argument |
Vector |
Vector.times(Vector x)
Return a new vector containing the element-wise product of the recipient and the argument |
Vector |
NamedVector.times(Vector x)
|
Vector |
AbstractVector.times(Vector x)
|
Vector |
AbstractMatrix.times(Vector v)
|
Vector |
VectorIterable.timesSquared(Vector v)
Convenience method for producing this.transpose().times(this.times(v)), which can be implemented with only one pass over the matrix, without making the transpose() call (which can be expensive if the matrix is sparse) |
Vector |
AbstractMatrix.timesSquared(Vector v)
|
Vector |
MatrixSlice.vector()
|
Vector |
SparseColumnMatrix.viewColumn(int column)
|
Vector |
PivotedMatrix.viewColumn(int column)
Return the column at the given index |
Vector |
MatrixView.viewColumn(int column)
|
Vector |
Matrix.viewColumn(int column)
Return a reference to a column. |
Vector |
AbstractMatrix.viewColumn(int column)
Returns a view of a row. |
Vector |
Matrix.viewDiagonal()
Returns a reference to the diagonal of a matrix. |
Vector |
DiagonalMatrix.viewDiagonal()
Provides a view of the diagonal of a matrix. |
Vector |
AbstractMatrix.viewDiagonal()
Provides a view of the diagonal of a matrix. |
Vector |
VectorView.viewPart(int offset,
int length)
|
Vector |
Vector.viewPart(int offset,
int length)
Return a new vector containing the subset of the recipient |
Vector |
NamedVector.viewPart(int offset,
int length)
|
Vector |
DenseVector.viewPart(int offset,
int length)
|
Vector |
AbstractVector.viewPart(int offset,
int length)
|
Vector |
SparseRowMatrix.viewRow(int row)
|
Vector |
SparseMatrix.viewRow(int row)
|
Vector |
PivotedMatrix.viewRow(int row)
Return the row at the given index |
Vector |
MatrixView.viewRow(int row)
|
Vector |
Matrix.viewRow(int row)
Return a reference to a row. |
Vector |
DenseMatrix.viewRow(int row)
|
Vector |
AbstractMatrix.viewRow(int row)
Returns a view of a row. |
Methods in org.apache.mahout.math with parameters of type Vector | |
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void |
DenseVector.addAll(Vector v)
|
double |
Vector.aggregate(Vector other,
DoubleDoubleFunction aggregator,
DoubleDoubleFunction combiner)
Generalized inner product - take two vectors, iterate over them both, using the combiner to combine together (and possibly map in some way) each pair of values, which are then aggregated with the previous accumulated value in the combiner. |
double |
NamedVector.aggregate(Vector other,
DoubleDoubleFunction aggregator,
DoubleDoubleFunction combiner)
|
double |
AbstractVector.aggregate(Vector other,
DoubleDoubleFunction aggregator,
DoubleDoubleFunction combiner)
|
Vector |
Vector.assign(Vector other)
Assign the other vector values to the receiver |
Vector |
SequentialAccessSparseVector.assign(Vector other)
|
Vector |
RandomAccessSparseVector.assign(Vector other)
|
Vector |
NamedVector.assign(Vector other)
|
Vector |
AbstractVector.assign(Vector other)
|
Vector |
Vector.assign(Vector other,
DoubleDoubleFunction function)
Apply the function to each element of the receiver and the corresponding element of the other argument |
Vector |
NamedVector.assign(Vector other,
DoubleDoubleFunction function)
|
Vector |
DenseVector.assign(Vector other,
DoubleDoubleFunction function)
|
Vector |
AbstractVector.assign(Vector other,
DoubleDoubleFunction function)
|
Matrix |
SparseRowMatrix.assignColumn(int column,
Vector other)
|
Matrix |
SparseMatrix.assignColumn(int column,
Vector other)
|
Matrix |
SparseColumnMatrix.assignColumn(int column,
Vector other)
|
Matrix |
RandomTrinaryMatrix.assignColumn(int column,
Vector other)
|
Matrix |
PivotedMatrix.assignColumn(int column,
Vector other)
Assign the other vector values to the column of the receiver |
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 |
DiagonalMatrix.assignColumn(int column,
Vector other)
|
Matrix |
DenseMatrix.assignColumn(int column,
Vector other)
|
Matrix |
SparseRowMatrix.assignRow(int row,
Vector other)
|
Matrix |
SparseMatrix.assignRow(int row,
Vector other)
|
Matrix |
SparseColumnMatrix.assignRow(int row,
Vector other)
|
Matrix |
RandomTrinaryMatrix.assignRow(int row,
Vector other)
|
Matrix |
PivotedMatrix.assignRow(int row,
Vector other)
Assign the other vector values to the row of the receiver |
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 |
DiagonalMatrix.assignRow(int row,
Vector other)
Assign the other vector values to the row of the receiver |
Matrix |
DenseMatrix.assignRow(int row,
Vector other)
|
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)
|
double |
Vector.dot(Vector x)
Return the dot product of the recipient and the argument |
double |
NamedVector.dot(Vector x)
|
double |
AbstractVector.dot(Vector x)
|
double |
VectorView.getDistanceSquared(Vector v)
|
double |
Vector.getDistanceSquared(Vector v)
Get the square of the distance between this vector and the other vector. |
double |
NamedVector.getDistanceSquared(Vector v)
|
double |
AbstractVector.getDistanceSquared(Vector v)
|
Vector |
Vector.minus(Vector x)
Return a new vector containing the element by element difference of the recipient and the argument |
Vector |
SequentialAccessSparseVector.minus(Vector that)
|
Vector |
NamedVector.minus(Vector x)
|
Vector |
AbstractVector.minus(Vector that)
|
static Vector |
Algebra.mult(Matrix m,
Vector v)
|
Vector |
Vector.plus(Vector x)
Return a new vector containing the element by element sum of the recipient and the argument |
Vector |
NamedVector.plus(Vector x)
|
Vector |
AbstractVector.plus(Vector x)
|
Vector |
VectorIterable.times(Vector v)
Return a new vector with cardinality equal to getNumRows() of this matrix which is the matrix product of the recipient and the argument |
Vector |
Vector.times(Vector x)
Return a new vector containing the element-wise product of the recipient and the argument |
Vector |
NamedVector.times(Vector x)
|
Vector |
AbstractVector.times(Vector x)
|
Vector |
AbstractMatrix.times(Vector v)
|
Vector |
VectorIterable.timesSquared(Vector v)
Convenience method for producing this.transpose().times(this.times(v)), which can be implemented with only one pass over the matrix, without making the transpose() call (which can be expensive if the matrix is sparse) |
Vector |
AbstractMatrix.timesSquared(Vector v)
|
Constructors in org.apache.mahout.math with parameters of type Vector | |
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DenseVector(Vector vector)
Copy-constructor (for use in turning a sparse vector into a dense one, for example) |
|
DiagonalMatrix(Vector values)
|
|
MatrixSlice(Vector v,
int index)
|
|
NamedVector(Vector delegate,
String name)
|
|
PermutedVectorView(Vector vector,
int[] pivot)
|
|
PermutedVectorView(Vector vector,
int[] pivot,
int[] unpivot)
|
|
RandomAccessSparseVector(Vector other)
|
|
SequentialAccessSparseVector(Vector other)
|
|
SparseRowMatrix(int rows,
int columns,
Vector[] rowVectors)
Construct a sparse matrix starting with the provided row vectors. |
|
SparseRowMatrix(int rows,
int columns,
Vector[] vectors,
boolean shallowCopy,
boolean randomAccess)
|
|
VectorView(Vector vector,
int offset,
int cardinality)
|
Uses of Vector in org.apache.mahout.math.als |
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Methods in org.apache.mahout.math.als that return Vector | |
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Vector |
AlternatingLeastSquaresSolver.solve(Iterable<Vector> featureVectors,
Vector ratingVector,
double lambda,
int numFeatures)
|
Vector |
ImplicitFeedbackAlternatingLeastSquaresSolver.solve(Vector ratings)
|
Methods in org.apache.mahout.math.als with parameters of type Vector | |
---|---|
Vector |
AlternatingLeastSquaresSolver.solve(Iterable<Vector> featureVectors,
Vector ratingVector,
double lambda,
int numFeatures)
|
Vector |
ImplicitFeedbackAlternatingLeastSquaresSolver.solve(Vector ratings)
|
Method parameters in org.apache.mahout.math.als with type arguments of type Vector | |
---|---|
Vector |
AlternatingLeastSquaresSolver.solve(Iterable<Vector> featureVectors,
Vector ratingVector,
double lambda,
int numFeatures)
|
Uses of Vector in org.apache.mahout.math.decomposer |
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Methods in org.apache.mahout.math.decomposer with parameters of type Vector | |
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protected EigenStatus |
AsyncEigenVerifier.innerVerify(VectorIterable corpus,
Vector vector)
|
EigenStatus |
SingularVectorVerifier.verify(VectorIterable eigenMatrix,
Vector vector)
|
EigenStatus |
SimpleEigenVerifier.verify(VectorIterable corpus,
Vector vector)
|
EigenStatus |
AsyncEigenVerifier.verify(VectorIterable corpus,
Vector vector)
|
Uses of Vector in org.apache.mahout.math.decomposer.hebbian |
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Methods in org.apache.mahout.math.decomposer.hebbian that return Vector | |
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Vector |
TrainingState.currentTrainingProjection()
|
Vector |
TrainingState.getHelperVector()
|
Vector |
TrainingState.mostRecentEigen()
|
Methods in org.apache.mahout.math.decomposer.hebbian with parameters of type Vector | |
---|---|
protected boolean |
HebbianSolver.hasNotConverged(Vector currentPseudoEigen,
Matrix corpus,
TrainingState state)
Uses the SingularVectorVerifier to check for convergence |
void |
TrainingState.setHelperVector(Vector helperVector)
|
void |
HebbianUpdater.update(Vector pseudoEigen,
Vector trainingVector,
TrainingState currentState)
|
void |
EigenUpdater.update(Vector pseudoEigen,
Vector trainingVector,
TrainingState currentState)
|
protected EigenStatus |
HebbianSolver.verify(Matrix corpus,
Vector currentPseudoEigen)
|
Uses of Vector in org.apache.mahout.math.decomposer.lanczos |
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Fields in org.apache.mahout.math.decomposer.lanczos with type parameters of type Vector | |
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protected Map<Integer,Vector> |
LanczosState.basis
|
protected Map<Integer,Vector> |
LanczosState.singularVectors
|
Methods in org.apache.mahout.math.decomposer.lanczos that return Vector | |
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Vector |
LanczosState.getBasisVector(int i)
|
Vector |
LanczosState.getRightSingularVector(int i)
|
Methods in org.apache.mahout.math.decomposer.lanczos with parameters of type Vector | |
---|---|
protected double |
LanczosSolver.calculateScaleFactor(Vector nextVector)
|
protected void |
LanczosSolver.orthoganalizeAgainstAllButLast(Vector nextVector,
LanczosState state)
|
void |
LanczosState.setBasisVector(int i,
Vector basisVector)
|
void |
LanczosState.setRightSingularVector(int i,
Vector vector)
|
Constructors in org.apache.mahout.math.decomposer.lanczos with parameters of type Vector | |
---|---|
LanczosState(VectorIterable corpus,
int desiredRank,
Vector initialVector)
|
Uses of Vector in org.apache.mahout.math.function |
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Methods in org.apache.mahout.math.function with parameters of type Vector | |
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double |
VectorFunction.apply(Vector f)
|
Uses of Vector in org.apache.mahout.math.matrix |
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Methods in org.apache.mahout.math.matrix that return Vector | |
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Vector |
DoubleMatrix1D.toVector()
Deprecated. |
Uses of Vector in org.apache.mahout.math.matrix.impl |
---|
Methods in org.apache.mahout.math.matrix.impl that return Vector | |
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Vector |
SparseDoubleMatrix1D.toVector()
Deprecated. |
Uses of Vector in org.apache.mahout.math.solver |
---|
Methods in org.apache.mahout.math.solver that return Vector | |
---|---|
Vector |
Preconditioner.precondition(Vector v)
Preconditions the specified vector. |
Vector |
JacobiConditioner.precondition(Vector v)
|
Vector |
LSMR.solve(Matrix A,
Vector b)
|
Vector |
ConjugateGradientSolver.solve(VectorIterable a,
Vector b)
Solves the system Ax = b with default termination criteria. |
Vector |
ConjugateGradientSolver.solve(VectorIterable a,
Vector b,
Preconditioner precond)
Solves the system Ax = b with default termination criteria using the specified preconditioner. |
Vector |
ConjugateGradientSolver.solve(VectorIterable a,
Vector b,
Preconditioner preconditioner,
int maxIterations,
double maxError)
Solves the system Ax = b, where A is a linear operator and b is a vector. |
Methods in org.apache.mahout.math.solver with parameters of type Vector | |
---|---|
Vector |
Preconditioner.precondition(Vector v)
Preconditions the specified vector. |
Vector |
JacobiConditioner.precondition(Vector v)
|
Vector |
LSMR.solve(Matrix A,
Vector b)
|
Vector |
ConjugateGradientSolver.solve(VectorIterable a,
Vector b)
Solves the system Ax = b with default termination criteria. |
Vector |
ConjugateGradientSolver.solve(VectorIterable a,
Vector b,
Preconditioner precond)
Solves the system Ax = b with default termination criteria using the specified preconditioner. |
Vector |
ConjugateGradientSolver.solve(VectorIterable a,
Vector b,
Preconditioner preconditioner,
int maxIterations,
double maxError)
Solves the system Ax = b, where A is a linear operator and b is a vector. |
Uses of Vector in org.apache.mahout.math.ssvd |
---|
Methods in org.apache.mahout.math.ssvd that return Vector | |
---|---|
Vector |
SequentialBigSvd.getSingularValues()
|
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