A B C D E F G H I J K L M N O P R S T U V W X Y

K

KAPPA_PROPERTY - Static variable in class edu.ucla.sspace.clustering.FastStreamingKMeans

The property for specifying kappa, the maximum number of facilities.

KEEP_SIMILARITY_MATRIX_IN_MEMORY_PROPERTY - Static variable in class edu.ucla.sspace.clustering.LinkClustering

The property to specify if the edge similarity matrix should be kept in memory during clustering, or if its values should be computed on the fly.

KEEP_WEIGHT_VECTORS_PROPERTY - Static variable in class edu.ucla.sspace.graph.WeightedLinkClustering

kendallsTau(double[], double[]) - Static method in class edu.ucla.sspace.common.Similarity

Computes Kendall's tau of the values in the two arrays.

kendallsTau(int[], int[]) - Static method in class edu.ucla.sspace.common.Similarity

Computes Kendall's tau of the values in the two arrays.

kendallsTau(Vector, Vector) - Static method in class edu.ucla.sspace.common.Similarity

Computes Kendall's tau of the values in the two vectors.

kendallsTau(DoubleVector, DoubleVector) - Static method in class edu.ucla.sspace.common.Similarity

Computes Kendall's tau of the values in the two vectors.

kendallsTau(IntegerVector, IntegerVector) - Static method in class edu.ucla.sspace.common.Similarity

Computes Kendall's tau of the values in the two vectors.

KendallsTau - Class in edu.ucla.sspace.similarity

A functional class for computing Kendall's tau of the values in the two vectors.

KendallsTau() - Constructor for class edu.ucla.sspace.similarity.KendallsTau

ket - Variable in class org.tartarus.snowball.SnowballProgram

keySet() - Method in class edu.ucla.sspace.basis.AbstractBasisMapping

Returns the set of keys known by this BasisMapping

keySet() - Method in interface edu.ucla.sspace.basis.BasisMapping

Returns the set of keys known by this BasisMapping

keySet() - Method in class edu.ucla.sspace.dv.PathBasedBasisMapping

Returns the set of keys known by this BasisMapping

keySet() - Method in class edu.ucla.sspace.dv.RelationPathBasisMapping

Returns the set of keys known by this BasisMapping

keySet() - Method in class edu.ucla.sspace.util.CharMap

Returns a Set view of the keys contained in this map.

keySet() - Method in class edu.ucla.sspace.util.GeneratorMap

keySet() - Method in class edu.ucla.sspace.util.HashBiMap

keySet() - Method in class edu.ucla.sspace.util.HashMultiMap

Returns a Set view of the mappings contained in this multi-map.

keySet() - Method in class edu.ucla.sspace.util.IntegerMap

Returns a Set view of the keys contained in this map.

keySet() - Method in interface edu.ucla.sspace.util.MultiMap

Returns a Set view of the mappings contained in this multi-map.

keySet() - Method in class edu.ucla.sspace.util.primitive.IntIntHashMultiMap

Returns a Set view of the mappings contained in this multi-map.

keySet() - Method in interface edu.ucla.sspace.util.primitive.IntIntMultiMap

Returns a Set view of the mappings contained in this multi-map.

keySet() - Method in class edu.ucla.sspace.util.TreeMultiMap

Returns a Set view of the mappings contained in this multi-map.

keySet() - Method in class edu.ucla.sspace.util.TrieMap

Returns a Set view of the keys contained in this map.

klDivergence(DoubleVector, DoubleVector) - Static method in class edu.ucla.sspace.common.Similarity

Computes the K-L Divergence of two probability distributions A and B where the vectors a and b correspond to n samples from each respective distribution.

klDivergence(IntegerVector, IntegerVector) - Static method in class edu.ucla.sspace.common.Similarity

Computes the K-L Divergence of two probability distributions A and B where the vectors a and b correspond to n samples from each respective distribution.

klDivergence(Vector, Vector) - Static method in class edu.ucla.sspace.common.Similarity

Computes the K-L Divergence of two probability distributions A and B where the vectors a and b correspond to n samples from each respective distribution.

klDivergence(double[], double[]) - Static method in class edu.ucla.sspace.common.Similarity

Computes the K-L Divergence of two probability distributions A and B where the vectors a and b correspond to n samples from each respective distribution.

klDivergence(int[], int[]) - Static method in class edu.ucla.sspace.common.Similarity

Computes the K-L Divergence of two probability distributions A and B where the vectors a and b correspond to n samples from each respective distribution.

KLDivergence - Class in edu.ucla.sspace.similarity

Returns the KL Divergence between any two probability distributions represented as Vectors.

KLDivergence() - Constructor for class edu.ucla.sspace.similarity.KLDivergence

kMeansObjective(int, int[], Matrix) - Static method in class edu.ucla.sspace.clustering.BaseSpectralCut

Returns the K-Means objective over an arbitrary clustering assignment for the data set.

KMeansPlusPlusSeed - Class in edu.ucla.sspace.clustering.seeding

This KMeansSeed implementation attempts to select centroids from the set of data points that are well scattered.

KMeansPlusPlusSeed() - Constructor for class edu.ucla.sspace.clustering.seeding.KMeansPlusPlusSeed

KMeansSeed - Interface in edu.ucla.sspace.clustering.seeding

An interface for KMeans seeding algorithms.

KOFL_PROPERTY - Static variable in class edu.ucla.sspace.clustering.StreamingKMeans

KrippendorffsAlpha - Class in edu.ucla.sspace.util

KrippendorffsAlpha() - Constructor for class edu.ucla.sspace.util.KrippendorffsAlpha

KrippendorffsAlpha.DifferenceFunction - Enum in edu.ucla.sspace.util

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