Uses of Interface
edu.ucla.sspace.similarity.SimilarityFunction

Packages that use SimilarityFunction

Package	Description
edu.ucla.sspace.clustering
edu.ucla.sspace.clustering.seeding
edu.ucla.sspace.common
edu.ucla.sspace.matrix
edu.ucla.sspace.similarity
edu.ucla.sspace.util

Uses of SimilarityFunction in edu.ucla.sspace.clustering

Fields in edu.ucla.sspace.clustering declared as SimilarityFunction

Modifier and Type	Field and Description
static SimilarityFunction	FastStreamingKMeans.DEFAULT_SIMILARITY_FUNCTION The default similarity function is in the inverse of the square of the Euclidean distances, which preserves all the properties specified in the Shindler et al (2011) paper.

Methods in edu.ucla.sspace.clustering with parameters of type SimilarityFunction

Modifier and Type	Method and Description
Assignments	Streemer.cluster(Matrix matrix, int numClusters, double backgroundClusterPerc, double similarityThreshold, int minClusterSize, SimilarityFunction simFunc)
Assignments	FastStreamingKMeans.cluster(Matrix matrix, int numClusters, int kappa, double beta, SimilarityFunction simFunc) Clusters the rows of the provided matrix into the specified number of clusters in a single pass using the parameters to guide how clusters are formed.

Constructors in edu.ucla.sspace.clustering with parameters of type SimilarityFunction

Constructor and Description
NeighborChainAgglomerativeClustering(NeighborChainAgglomerativeClustering.ClusterLink method, SimilarityFunction simFunc) Creates a NeighborChainAgglomerativeClustering with the specified minimum similarity threshold.

Uses of SimilarityFunction in edu.ucla.sspace.clustering.seeding

Constructors in edu.ucla.sspace.clustering.seeding with parameters of type SimilarityFunction

Constructor and Description
GeneralizedOrssSeed(SimilarityFunction simFunc)

Uses of SimilarityFunction in edu.ucla.sspace.common

Methods in edu.ucla.sspace.common that return SimilarityFunction

Modifier and Type	Method and Description
static SimilarityFunction	Similarity.getSimilarityFunction(Similarity.SimType similarityType)

Uses of SimilarityFunction in edu.ucla.sspace.matrix

Methods in edu.ucla.sspace.matrix with parameters of type SimilarityFunction

Modifier and Type	Method and Description
SortedMultiMap<Double,Integer>	RowComparator.getMostSimilar(Matrix m, int row, int kNearestRows, SimilarityFunction simFunction) Compares the specified row to all other rows, returning the k-nearest rows according to the similarity metric.
void	MinSimilarityAffinityMatrixCreator.setFunctions(SimilarityFunction edgeSim, SimilarityFunction kernelSim) Sets the SimilarityFunctions to be used for selecting edges and then weighting edges.
void	AffinityMatrixCreator.setFunctions(SimilarityFunction edgeSim, SimilarityFunction kernelSim) Sets the SimilarityFunctions to be used for selecting edges and then weighting edges.
void	NearestNeighborAffinityMatrixCreator.setFunctions(SimilarityFunction edgeSim, SimilarityFunction kernelSim) Sets the SimilarityFunctions to be used for selecting edges and then weighting edges.

Uses of SimilarityFunction in edu.ucla.sspace.similarity

Classes in edu.ucla.sspace.similarity that implement SimilarityFunction

Modifier and Type	Class and Description
class	AbstractSymmetricSimilarityFunction A base implementation for any symmetic SimilarityFunction that requires no parameters.
class	AverageCommonFeatureRank Computes the Average Common Feature Rank between two feature vectors.
class	CosineSimilarity Returns the cosine similarity between any two Vectors.
class	DotProduct Returns the dot product of the two vectors.
class	EuclideanSimilarity Returns the Euclidean Similarity between any two Vectors.
class	GaussianKernel Returns the Gaussing kernel weighting of two vectors using a parameter to weight the distance between the two vectors.
class	JaccardIndex Returns the Jaccard Index between any two Vectors.
class	KendallsTau A functional class for computing Kendall's tau of the values in the two vectors.
class	KLDivergence Returns the KL Divergence between any two probability distributions represented as Vectors.
class	LinSimilarity Returns the Lin Similarity between any two Vectors.
class	OneSimilarity Returns 1, always.
class	PearsonCorrelation Returns the Pearson Correlation between any two Vectors.
class	PolynomialKernel Returns the dot product of the two vectors raised to a specified power.
class	SpearmanRankCorrelation Returns the Spearman Rank Correlation between any two Vectors.
class	TanimotoCoefficient Returns the Tanimoto Coefficient between any two Vectors.

Uses of SimilarityFunction in edu.ucla.sspace.util

Constructors in edu.ucla.sspace.util with parameters of type SimilarityFunction

Constructor and Description
SimpleNearestNeighborFinder(SemanticSpace sspace, SimilarityFunction similarity) Creates this SimpleNearestNeighborFinder with as many threads as processings and using the provided similarity function to compare words.
SimpleNearestNeighborFinder(SemanticSpace sspace, SimilarityFunction similarity, int numThreads) Creates this SimpleNearestNeighborFinder with the specified number of threads and using the provided similarity function to compare words.