Uses of Interface
org.tribuo.math.la.SGDVector

Packages that use SGDVector

Package	Description
org.tribuo.classification.sgd	Provides infrastructure for Stochastic Gradient Descent for classification problems.
org.tribuo.classification.sgd.objectives	Provides classification loss functions for Stochastic Gradient Descent.
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.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.
org.tribuo.regression.sgd	Provides infrastructure for Stochastic Gradient Descent based regression models.
org.tribuo.regression.sgd.objectives	Provides regression loss functions for Stochastic Gradient Descent.

Uses of SGDVector in org.tribuo.classification.sgd

Methods in org.tribuo.classification.sgd that return types with arguments of type SGDVector

Modifier and Type	Method and Description
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	LabelObjective.valueAndGradient(int truth, SGDVector prediction) Scores a prediction, returning the loss and a vector of per label gradients.

Methods in org.tribuo.classification.sgd with parameters of type SGDVector

Modifier and Type	Method and Description
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	LabelObjective.valueAndGradient(int truth, SGDVector prediction) Scores a prediction, returning the loss and a vector of per label gradients.

Uses of SGDVector in org.tribuo.classification.sgd.objectives

Methods in org.tribuo.classification.sgd.objectives that return types with arguments of type SGDVector

Modifier and Type	Method and Description
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	LogMulticlass.valueAndGradient(int truth, SGDVector prediction) Returns a Pair of Double and the supplied prediction vector.
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	Hinge.valueAndGradient(int truth, SGDVector prediction) Returns a Pair of Double and SparseVector.

Methods in org.tribuo.classification.sgd.objectives with parameters of type SGDVector

Modifier and Type	Method and Description
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	LogMulticlass.valueAndGradient(int truth, SGDVector prediction) Returns a Pair of Double and the supplied prediction vector.
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	Hinge.valueAndGradient(int truth, SGDVector prediction) Returns a Pair of Double and SparseVector.

Uses of SGDVector in org.tribuo.math

Methods in org.tribuo.math that return SGDVector

Modifier and Type	Method and Description
SGDVector	LinearParameters.predict(SparseVector example) Generates an unnormalised prediction by leftMultiply'ing the weights with the incoming features.

Method parameters in org.tribuo.math with type arguments of type SGDVector

Modifier and Type	Method and Description
Tensor[]	LinearParameters.gradients(com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector> score, SparseVector features) Generate the gradients for a particular feature vector given the loss and the per output gradients.

Uses of SGDVector in org.tribuo.math.la

Classes in org.tribuo.math.la that implement SGDVector

Modifier and Type	Class and Description
class	DenseVector A dense vector, backed by a double array.
class	SparseVector A sparse vector.

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

Modifier and Type	Method and Description
SGDVector	SparseVector.add(SGDVector other) Adds other to this vector, producing a new SGDVector.
SGDVector	SGDVector.add(SGDVector other) Adds other to this vector, producing a new SGDVector.
SGDVector	SGDVector.copy() Returns a deep copy of this vector.
SGDVector	Matrix.getRow(int i) Extract a row as an SGDVector.
SGDVector	Matrix.leftMultiply(SGDVector input) Multiplies this Matrix by a SGDVector returning a vector of the appropriate size.
SGDVector	Matrix.rightMultiply(SGDVector input) Multiplies this Matrix by a SGDVector returning a vector of the appropriate size.
SGDVector	SGDVector.scale(double coefficient) Generates a new vector with each element scaled by coefficient.
SGDVector	SparseVector.subtract(SGDVector other) Subtracts other from this vector, producing a new SGDVector.
SGDVector	SGDVector.subtract(SGDVector other) Subtracts other from this vector, producing a new SGDVector.

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

Modifier and Type	Method and Description
SGDVector	SparseVector.add(SGDVector other) Adds other to this vector, producing a new SGDVector.
SGDVector	SGDVector.add(SGDVector other) Adds other to this vector, producing a new SGDVector.
DenseVector	DenseVector.add(SGDVector other) Adds other to this vector, producing a new DenseVector.
void	DenseMatrix.broadcastIntersectAndAddInPlace(SGDVector input, boolean broadcastOverDim1) Broadcasts the input vector and adds it to each row/column of the matrix.
default double	SGDVector.cosineDistance(SGDVector other) Calculates the cosine distance of two vectors.
default double	SGDVector.cosineSimilarity(SGDVector other) Calculates the cosine similarity of two vectors.
double	SparseVector.distance(SGDVector other, DoubleUnaryOperator transformFunc, DoubleUnaryOperator normalizeFunc)
double	SparseVector.dot(SGDVector other)
double	SGDVector.dot(SGDVector other) Calculates the dot product between this vector and other.
double	DenseVector.dot(SGDVector other)
double	SparseVector.euclideanDistance(SGDVector other)
double	SGDVector.euclideanDistance(SGDVector other) The l2 or euclidean distance between this vector and the other vector.
double	DenseVector.euclideanDistance(SGDVector other) The l2 or euclidean distance between this vector and the other vector.
double	SparseVector.l1Distance(SGDVector other)
double	SGDVector.l1Distance(SGDVector other) The l1 or Manhattan distance between this vector and the other vector.
double	DenseVector.l1Distance(SGDVector other) The l1 or Manhattan distance between this vector and the other vector.
default double	SGDVector.l2Distance(SGDVector other) Synonym for euclideanDistance.
SGDVector	Matrix.leftMultiply(SGDVector input) Multiplies this Matrix by a SGDVector returning a vector of the appropriate size.
DenseVector	DenseSparseMatrix.leftMultiply(SGDVector input)
DenseVector	DenseMatrix.leftMultiply(SGDVector input)
Matrix	SparseVector.outer(SGDVector other) This generates the outer product when dotted with another SparseVector.
Matrix	SGDVector.outer(SGDVector other) Generates the matrix representing the outer product between the two vectors.
Matrix	DenseVector.outer(SGDVector other)
SGDVector	Matrix.rightMultiply(SGDVector input) Multiplies this Matrix by a SGDVector returning a vector of the appropriate size.
DenseVector	DenseSparseMatrix.rightMultiply(SGDVector input) rightMultiply is very inefficient on DenseSparseMatrix due to the storage format.
DenseVector	DenseMatrix.rightMultiply(SGDVector input)
SGDVector	SparseVector.subtract(SGDVector other) Subtracts other from this vector, producing a new SGDVector.
SGDVector	SGDVector.subtract(SGDVector other) Subtracts other from this vector, producing a new SGDVector.
DenseVector	DenseVector.subtract(SGDVector other) Subtracts other from this vector, producing a new DenseVector.

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

Classes in org.tribuo.math.optimisers.util that implement SGDVector

Modifier and Type	Class and 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 with parameters of type SGDVector

Modifier and Type	Method and Description
double	ShrinkingVector.dot(SGDVector other)
DenseVector	ShrinkingMatrix.leftMultiply(SGDVector input)

Uses of SGDVector in org.tribuo.regression.sgd

Methods in org.tribuo.regression.sgd that return types with arguments of type SGDVector

Modifier and Type	Method and Description
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	RegressionObjective.loss(DenseVector truth, SGDVector prediction) Scores a prediction, returning the loss.

Methods in org.tribuo.regression.sgd with parameters of type SGDVector

Modifier and Type	Method and Description
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	RegressionObjective.loss(DenseVector truth, SGDVector prediction) Scores a prediction, returning the loss.

Uses of SGDVector in org.tribuo.regression.sgd.objectives

Methods in org.tribuo.regression.sgd.objectives that return types with arguments of type SGDVector

Modifier and Type	Method and Description
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	SquaredLoss.loss(DenseVector truth, SGDVector prediction)
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	Huber.loss(DenseVector truth, SGDVector prediction)
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	AbsoluteLoss.loss(DenseVector truth, SGDVector prediction)

Methods in org.tribuo.regression.sgd.objectives with parameters of type SGDVector

Modifier and Type	Method and Description
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	SquaredLoss.loss(DenseVector truth, SGDVector prediction)
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	Huber.loss(DenseVector truth, SGDVector prediction)
com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector>	AbsoluteLoss.loss(DenseVector truth, SGDVector prediction)