Uses of Interface
edu.umass.cs.mallet.base.types.Vector

Packages that use Vector

Package	Description
edu.umass.cs.mallet.base.types

Uses of Vector in edu.umass.cs.mallet.base.types

Classes in edu.umass.cs.mallet.base.types that implement Vector

Modifier and Type	Class and Description
class	AugmentableFeatureVector
class	DenseFeatureVector
class	DenseVector
class	ExpGain
class	FeatureCounts
class	FeatureVector A subset of an Alphabet in which each element of the subset has an associated value.
class	GainRatio List of features along with their thresholds sorted in descending order of the ratio of (1) information gained by splitting instances on the feature at its associated threshold value, to (2) the split information.
class	GradientGain
class	HashedSparseVector
class	IndexedSparseVector
class	InfoGain
class	KLGain
class	LabelVector
class	Multinomial A probability distribution over a set of features represented as a FeatureVector.
static class	Multinomial.Logged A Multinomial in which the values associated with each feature index fi is Math.log(probability[fi]) instead of probability[fi].
class	PartiallyRankedFeatureVector
class	RankedFeatureVector
class	SparseVector A vector that allocates memory only for non-zero values.

Methods in edu.umass.cs.mallet.base.types with parameters of type Vector

Modifier and Type	Method and Description
void	Matrix2.columnPlusEquals(int ci, Vector v, double factor)
double	FeatureVectorSequence.dotProduct(int sequencePosition, Vector weights)
static double	MatrixOps.rowDotProduct(double[] m, int nc, int ri, Vector v, double factor, int maxCi, FeatureSelection selection)
static double	MatrixOps.rowDotProduct(double[] m, int nc, int ri, Vector v, int maxCi, FeatureSelection selection)
double	Matrix2.rowDotProduct(int ri, Vector v)
double	Matrix2.rowDotProduct(int ri, Vector v, int maxCi, FeatureSelection selection) Skip all column indices higher than "maxCi".
static void	MatrixOps.rowPlusEquals(double[] m, int nc, int ri, Vector v, double factor)
void	Matrix2.rowPlusEquals(int ri, Vector v, double factor)
static double	MatrixOps.sum(Vector v)