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

Packages that use DenseMatrix

Package	Description
org.tribuo.classification.sgd.crf	Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
org.tribuo.common.sgd	Provides the base classes for models trained with stochastic gradient descent.
org.tribuo.interop.oci	Code for uploading models to Oracle Cloud Infrastructure Data Science, and also for scoring models deployed in Oracle Cloud Infrastructure Data Science.
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 DenseMatrix in org.tribuo.classification.sgd.crf

Fields in org.tribuo.classification.sgd.crf declared as DenseMatrix

Modifier and Type	Field	Description
final DenseMatrix	ChainHelper.ChainCliqueValues.transitionValues	The label-label transition matrix.

Uses of DenseMatrix in org.tribuo.common.sgd

Methods in org.tribuo.common.sgd that return DenseMatrix

Modifier and Type	Method	Description
DenseMatrix	AbstractFMModel.getLinearWeightsCopy()	Returns a copy of the linear weights.
DenseMatrix	AbstractLinearSGDModel.getWeightsCopy()	Returns a copy of the weights.

Uses of DenseMatrix in org.tribuo.interop.oci

Methods in org.tribuo.interop.oci that return DenseMatrix

Modifier and Type	Method	Description
protected DenseMatrix	OCIModel.convertFeatures(SparseVector sparseVector)
protected DenseMatrix	OCIModel.convertFeaturesList(List<SparseVector> list)
protected DenseMatrix	OCIModel.externalPrediction(DenseMatrix features)

Methods in org.tribuo.interop.oci with parameters of type DenseMatrix

Modifier and Type	Method	Description
List<Prediction<Label>>	OCILabelConverter.convertOutput(DenseMatrix scores, int[] numValidFeatures, List<Example<Label>> examples, ImmutableOutputInfo<Label> outputIDInfo)
protected List<Prediction<T>>	OCIModel.convertOutput(DenseMatrix scores, int[] numValidFeatures, List<Example<T>> list)
protected Prediction<T>	OCIModel.convertOutput(DenseMatrix scores, int numValidFeature, Example<T> example)
List<Prediction<MultiLabel>>	OCIMultiLabelConverter.convertOutput(DenseMatrix scores, int[] numValidFeatures, List<Example<MultiLabel>> examples, ImmutableOutputInfo<MultiLabel> outputIDInfo)
List<Prediction<T>>	OCIOutputConverter.convertOutput(DenseMatrix scores, int[] numValidFeatures, List<Example<T>> examples, ImmutableOutputInfo<T> outputIDInfo)	Converts a dense matrix into a list of predictions of the appropriate type.
List<Prediction<Regressor>>	OCIRegressorConverter.convertOutput(DenseMatrix scores, int[] numValidFeatures, List<Example<Regressor>> examples, ImmutableOutputInfo<Regressor> outputIDInfo)
protected DenseMatrix	OCIModel.externalPrediction(DenseMatrix features)

Uses of DenseMatrix in org.tribuo.math

Methods in org.tribuo.math that return DenseMatrix

Modifier and Type	Method	Description
DenseMatrix	LinearParameters.getWeightMatrix()	Returns the weight matrix.

Constructors in org.tribuo.math with parameters of type DenseMatrix

Modifier	Constructor	Description
	LinearParameters(DenseMatrix weightMatrix)	Constructs a LinearParameters wrapped around a weight matrix.

Uses of DenseMatrix in org.tribuo.math.distributions

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

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 DenseMatrix in org.tribuo.math.la

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

Modifier and Type	Method	Description
DenseMatrix	DenseMatrix.copy()	Copies the matrix.
static DenseMatrix	DenseMatrix.createDenseMatrix(double[][] values)	Defensively copies the values before construction.
static DenseMatrix	DenseMatrix.createDenseMatrix(SGDVector[] vectors)	Constructs a new DenseMatrix copying the values from the supplied vectors.
static DenseMatrix	DenseMatrix.deserializeFromProto(int version, String className, com.google.protobuf.Any message)	Deserialization factory.
DenseMatrix	DenseMatrix.EigenDecomposition.eigenvectors()	The eigenvectors for each eigenvalue, stored in the columns of the matrix.
DenseMatrix	DenseMatrix.EigenDecomposition.householderMatrix()	The Householder matrix produced during the tridiagonalisation.
DenseMatrix	DenseMatrix.CholeskyFactorization.lMatrix()	The lower triangular factorized matrix.
DenseMatrix	DenseMatrix.LUFactorization.lower()	The lower triangular matrix, with ones on the diagonal.
DenseMatrix	DenseMatrix.matrixMultiply(Matrix other)
DenseMatrix	DenseMatrix.matrixMultiply(Matrix other, boolean transposeThis, boolean transposeOther)
DenseMatrix	DenseSparseMatrix.matrixMultiply(Matrix other)
DenseMatrix	DenseSparseMatrix.matrixMultiply(Matrix other, boolean transposeThis, boolean transposeOther)
DenseMatrix	DenseMatrix.selectColumns(int[] columnIndices)	Returns a new DenseMatrix containing a copy of the selected columns.
DenseMatrix	DenseMatrix.selectColumns(List<Integer> columnIndices)	Returns a new DenseMatrix containing a copy of the selected columns.
DenseMatrix	DenseMatrix.CholeskyFactorization.solve(Matrix matrix)	Solves the system A * X = B, where B is the input matrix, and A is the matrix which produced this Cholesky factorization.
DenseMatrix	DenseMatrix.EigenDecomposition.solve(Matrix matrix)	Solves the system A * X = Y, where Y is the input matrix, and A is the matrix which produced this eigen decomposition.
DenseMatrix	DenseMatrix.LUFactorization.solve(Matrix matrix)	Solves the system A * X = Y, where Y is the input matrix, and A is the matrix which produced this LU factorization.
DenseMatrix	DenseMatrix.transpose()	Returns a transposed copy of this matrix.
protected static DenseMatrix	DenseMatrix.unpackProto(org.tribuo.math.protos.DenseTensorProto proto)	Unpacks a DenseTensorProto into a DenseMatrix.
DenseMatrix	DenseMatrix.LUFactorization.upper()	The upper triangular matrix.

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

Modifier	Constructor	Description
	DenseMatrix(DenseMatrix other)	Copies the supplied matrix.

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

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

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

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

Modifier and Type	Method	Description
DenseMatrix	ShrinkingMatrix.convertToDense()

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

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