Package jsat.clustering

Interface Summary

Interface	Description
Clusterer	Defines the interface for a generic clustering algorithm.
KClusterer	Defines a clustering method that requires the number of clusters in the data set to be known before hand.

Class Summary

Class	Description
CLARA
ClustererBase	A base foundation that provides an implementation of Clusterer.cluster(jsat.DataSet) and #cluster(jsat.DataSet, java.util.concurrent.ExecutorService) using their int array counterparts.
DBSCAN	A density-based algorithm for discovering clusters in large spatial databases with noise (1996) by Martin Ester , Hans-peter Kriegel , Jörg S , Xiaowei Xu
EMGaussianMixture	An implementation of Gaussian Mixture models that learns the specified number of Gaussians using Expectation Maximization algorithm.
FLAME	Provides an implementation of the FLAME clustering algorithm.
GapStatistic	This class implements a method for estimating the number of clusters in a data set called the Gap Statistic.
HDBSCAN	HDBSCAN is a density based clustering algorithm that is an improvement over DBSCAN.
KClustererBase	A base foundation that provides an implementation of the methods that return a list of lists for the clusterings using their int array counterparts.
LSDBC	A parallel implementation of Locally Scaled Density Based Clustering.
MeanShift	The MeanShift algorithms performs clustering on a data set by letting the data speak for itself and performing a mode search amongst the data set, returning a cluster for each discovered mode.
MEDDIT
OPTICS	An Implementation of the OPTICS algorithm, which is a generalization of DBSCAN.
PAM
SeedSelectionMethods	This class provides methods for sampling a data set for a set of initial points to act as the seeds for a clustering algorithm.
TRIKMEDS	This class implements the TRIKMEDS algorithm for PAM clustering.

Enum Summary

Enum	Description
OPTICS.ExtractionMethod	Enum to indicate which method of extracting clusters should be used on the reachability plot.
SeedSelectionMethods.SeedSelection

Exception Summary

Exception	Description
ClusterFailureException	A ClusterFailureException is thrown when a clustering method is unable to perform its clustering for some reason.