Package edu.ucla.sspace.clustering

Interface Summary

Interface	Description
Assignment	A cluster assignment for a data point.
Cluster<T extends DoubleVector>	An interface for representing a single cluster, which is composed of several data points.
Clustering	An interface for any Ofline clustering implementation.
EigenCut	An interface for computing the spectral cut of a Matrix.
OnlineClustering<T extends DoubleVector>	An interface for any Online clustering implementation.

Class Summary

Class	Description
Assignments	The return value for all Clustering implementations.
AutomaticStopClustering	A Clustering implementation that iteratively computes the k-means clustering of a data set and fines the value of k that produced the most significant advantage compared to other values of k.
BaseSpectralCut	An abstract class for computing a spectral cut over a data Matrix that represents a set of data points.
BaseSpectralCut.Index	A simple comparable data struct holding a row vector's weight and the vector's original index in a matrix.
BisectingKMeans	An implementation of the Bisecting K-Means algorithm, also known as Repeated Bisections.
CentroidCluster<T extends DoubleVector>	This Cluster represents only the centroid of the data points assigned to it.
CKVWSpectralClustering03	A spectral clustering implementation based on the following paper: David Cheng , Ravi Kannan , Santosh Vempala , Grant Wang (2003) On a Recursive Spectral Algorithm for Clustering from Pairwise Similaritie.
CKVWSpectralClustering06	A spectral clustering implementation based on the following paper: David Cheng , Ravi Kannan , Santosh Vempala , Grant Wang (2003) A Divid-and-Merge Methodology for Clustering.
ClusteringByCommittee	An implementation of the Clustering by Committee (CBC) algorithm.
ClutoClustering	A class for interacting with the CLUTO clustering library.
DataMatrixLinkClustering
DirectClustering	An implementation of the Direct K-Means clustering available in the CLUTO Clustering Software.
FastStreamingKMeans	An implementation of Shindler's streaming K Means algorithm.
GapStatistic	A Clustering implementation that iteratively computes the k-means clustering of a data set and compares it to a random sample of reference data points.
HardAssignment	An implementation of a Assignment where a data point may be assigned to at most one cluster, i.e.
HierarchicalAgglomerativeClustering	A utility class for performing Hierarchical Agglomerative Clustering on matrix data in a file.
LinkClustering	An implmentation of the link clustering described in Ahn, Bagrow, and Lehman (2010).
LinkClustering.Edge	A utility data structure for representing a directed edge between two ordinally labeled nodes.
Merge	A status object that represents the result of agglomeratively merging two clusters.
NeighborChainAgglomerativeClustering	A Nearest Neighbor Chain Agglomerative Clustering implementation.
NeighborChainAgglomerativeClustering.Link	A simple struct for storing links between two clusters.
OnlineKMeans<T extends DoubleVector>	A Generator class for generating a new OnlineKMeansClustering instance.
SoftAssignment	A set of soft assignment.
SpectralClustering	Implementation of Spectral Clustering using divide and merge methodology.
StreamingKMeans<T extends DoubleVector>	An implementation of a simple, highly accurate streaming K Means algorithm.
Streemer	An implementation of the Streemer (Streaming EM) algorithm for foreground/background clustering.
SynchronizedCluster<T extends DoubleVector>	A synchronized decorator for Clusters.

Enum Summary

Enum	Description
AutomaticStopClustering.Measure	The available stopping criteria.
ClutoClustering.Criterion	The crition function by which CLUTO should evaluate the clustering assignment.
ClutoClustering.Method	The method by which CLUTO should cluster the data points
HierarchicalAgglomerativeClustering.ClusterLinkage	The method to use when comparing the similarity of two clusters.
NeighborChainAgglomerativeClustering.ClusterLink	The similarity method used when comparing and merging compelte clusters.