Package org.hipparchus.clustering

package org.hipparchus.clustering

Clustering algorithms.

Related Packages

Package	Description
org.hipparchus	Common classes used throughout the Hipparchus library.
org.hipparchus.clustering.distance	Common distance measures.
org.hipparchus.clustering.evaluation	Cluster evaluation methods.

Class	Description
CentroidCluster<T extends Clusterable>	A Cluster used by centroid-based clustering algorithms.
Cluster<T extends Clusterable>	Cluster holding a set of Clusterable points.
Clusterable	Interface for n-dimensional points that can be clustered together.
Clusterer<T extends Clusterable>	Base class for clustering algorithms.
DBSCANClusterer<T extends Clusterable>	DBSCAN (density-based spatial clustering of applications with noise) algorithm.
DoublePoint	A simple implementation of Clusterable for points with double coordinates.
FuzzyKMeansClusterer<T extends Clusterable>	Fuzzy K-Means clustering algorithm.
KMeansPlusPlusClusterer<T extends Clusterable>	Clustering algorithm based on David Arthur and Sergei Vassilvitski k-means++ algorithm.
KMeansPlusPlusClusterer.EmptyClusterStrategy	Strategies to use for replacing an empty cluster.
LocalizedClusteringFormats	Enumeration for localized messages formats used in exceptions messages.
MultiKMeansPlusPlusClusterer<T extends Clusterable>	A wrapper around a k-means++ clustering algorithm which performs multiple trials and returns the best solution.