Package org.hipparchus.clustering

Clustering algorithms.

See: Description

Interface Summary

Interface	Description
Clusterable	Interface for n-dimensional points that can be clustered together.

Class Summary

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.
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.
MultiKMeansPlusPlusClusterer<T extends Clusterable>	A wrapper around a k-means++ clustering algorithm which performs multiple trials and returns the best solution.

Enum Summary

Enum	Description
KMeansPlusPlusClusterer.EmptyClusterStrategy	Strategies to use for replacing an empty cluster.
LocalizedClusteringFormats	Enumeration for localized messages formats used in exceptions messages.

Package org.hipparchus.clustering Description

Clustering algorithms.