Uses of Class
org.tribuo.math.la.DenseVector

Packages that use DenseVector

Package	Description
org.tribuo.math	Contains the implementation of Tribuo's math library, it's gradient descent optimisers, kernels and a set of math related utils.
org.tribuo.math.distributions	A package of statistical distributions.
org.tribuo.math.la	Provides a linear algebra system used for numerical operations in Tribuo.
org.tribuo.math.optimisers.util	Provides some utility tensors for use in gradient optimisers.

Uses of DenseVector in org.tribuo.math

Methods in org.tribuo.math that return DenseVector

Modifier and Type	Method	Description
DenseVector	FeedForwardParameters.predict(SGDVector example)	Generates an un-normalized prediction by feeding the features through the parameters.
DenseVector	LinearParameters.predict(SGDVector example)	Generates an unnormalised prediction by leftMultiply'ing the weights with the incoming features.

Uses of DenseVector in org.tribuo.math.distributions

Methods in org.tribuo.math.distributions that return DenseVector

Modifier and Type	Method	Description
DenseVector	MultivariateNormalDistribution.sampleVector()	Sample a vector from this multivariate normal distribution.

Constructors in org.tribuo.math.distributions with parameters of type DenseVector

Modifier	Constructor	Description
	MultivariateNormalDistribution(DenseVector means, DenseMatrix covariance, long seed)	Constructs a multivariate normal distribution that can be sampled from.
	MultivariateNormalDistribution(DenseVector means, DenseMatrix covariance, long seed, boolean eigenDecomposition)	Constructs a multivariate normal distribution that can be sampled from.

Uses of DenseVector in org.tribuo.math.la

Methods in org.tribuo.math.la that return DenseVector

Modifier and Type	Method	Description
DenseVector	DenseVector.add(SGDVector other)	Adds other to this vector, producing a new DenseVector.
DenseVector	DenseMatrix.columnSum()	Returns a dense vector containing each column sum.
DenseVector	DenseVector.copy()
static DenseVector	DenseVector.createDenseVector(double[] values)	Defensively copies the values before construction.
static <T extends Output<T>> DenseVector	DenseVector.createDenseVector(Example<T> example, ImmutableFeatureMap featureInfo, boolean addBias)	Builds a DenseVector from an Example.
DenseVector	SparseVector.densify()	Returns a dense vector copying this sparse vector.
static DenseVector	DenseVector.deserializeFromProto(int version, String className, com.google.protobuf.Any message)	Deserialization factory.
DenseVector	DenseMatrix.EigenDecomposition.diagonal()	The diagonal vector of the tridiagonal form.
DenseVector	DenseMatrix.EigenDecomposition.eigenvalues()	The vector of eigenvalues, in descending order.
DenseVector	DenseVector.foreach(DoubleUnaryOperator f)	Applies the function f to each element of this vector returning a new vector.
DenseVector	DenseMatrix.gatherAcrossDim1(int[] elements)	Constructs a dense vector by gathering values across dimension 1.
DenseVector	DenseMatrix.gatherAcrossDim2(int[] elements)	Constructs a dense vector by gathering values across dimension 2.
DenseVector	DenseMatrix.getColumn(int index)	Returns a copy of the specified column.
DenseVector	DenseMatrix.EigenDecomposition.getEigenVector(int i)	Returns the dense vector representing the i'th eigenvector.
DenseVector	DenseMatrix.getRow(int i)
DenseVector	DenseMatrix.leftMultiply(SGDVector input)
DenseVector	DenseSparseMatrix.leftMultiply(SGDVector input)
DenseVector	DenseMatrix.EigenDecomposition.offDiagonal()	The off diagonal vector, with the first element set to zero.
DenseVector	DenseMatrix.rightMultiply(SGDVector input)
DenseVector	DenseSparseMatrix.rightMultiply(SGDVector input)	rightMultiply is very inefficient on DenseSparseMatrix due to the storage format.
DenseVector	DenseMatrix.rowSum()
DenseVector	DenseSparseMatrix.rowSum()
DenseVector	Matrix.rowSum()	Generates a DenseVector representing the sum of each row.
DenseVector	DenseVector.scale(double coefficient)
DenseVector	DenseMatrix.CholeskyFactorization.solve(SGDVector vector)	Solves a system of linear equations A * b = y, where y is the input vector, A is the matrix which produced this Cholesky factorization, and b is the returned value.
DenseVector	DenseMatrix.EigenDecomposition.solve(SGDVector vector)	Solves a system of linear equations A * b = y, where y is the input vector, A is the matrix which produced this eigen decomposition, and b is the returned value.
DenseVector	DenseMatrix.LUFactorization.solve(SGDVector vector)	Solves a system of linear equations A * b = y, where y is the input vector, A is the matrix which produced this LU factorization, and b is the returned value.
DenseVector	DenseVector.subtract(SGDVector other)	Subtracts other from this vector, producing a new DenseVector.
protected static DenseVector	DenseVector.unpackProto(org.tribuo.math.protos.DenseTensorProto proto)	Unpacks a DenseTensorProto into a DenseVector.

Methods in org.tribuo.math.la with parameters of type DenseVector

Modifier and Type	Method	Description
void	DenseMatrix.rowScaleInPlace(DenseVector scalingCoefficients)
void	DenseSparseMatrix.rowScaleInPlace(DenseVector scalingCoefficients)
void	Matrix.rowScaleInPlace(DenseVector scalingCoefficients)	Scales each row by the appropriate value in the DenseVector.
void	DenseVector.setElements(DenseVector other)	Sets all the elements of this vector to be the same as other.

Constructors in org.tribuo.math.la with parameters of type DenseVector

Modifier	Constructor	Description
protected	DenseVector(DenseVector other)	Copy constructor.

Uses of DenseVector in org.tribuo.math.optimisers.util

Subclasses of DenseVector in org.tribuo.math.optimisers.util

Modifier and Type	Class	Description
class	ShrinkingVector	A subclass of DenseVector which shrinks the value every time a new value is added.

Methods in org.tribuo.math.optimisers.util that return DenseVector

Modifier and Type	Method	Description
DenseVector	ShrinkingVector.convertToDense()
DenseVector	ShrinkingMatrix.leftMultiply(SGDVector input)

Constructors in org.tribuo.math.optimisers.util with parameters of type DenseVector

Modifier	Constructor	Description
	ShrinkingVector(DenseVector v, double baseRate, boolean scaleShrinking)	Constructs a shrinking vector copy of the supplied dense matrix.
	ShrinkingVector(DenseVector v, double baseRate, double lambda)	Constructs a shrinking vector copy of the supplied dense vector.