# Package org.apache.commons.math3.stat.clustering

Clustering algorithms

See: Description

- Interface Summary
  Interface | Description
  --- | ---
  Clusterable<T> | Interface for points that can be clustered together.

- Class Summary
  Class | Description
  --- | ---
  Cluster<T extends Clusterable<T>> | Cluster holding a set of `Clusterable` points.
  DBSCANClusterer<T extends Clusterable<T>> | DBSCAN (density-based spatial clustering of applications with noise) algorithm.
  EuclideanDoublePoint | A simple implementation of `Clusterable` for points with double coordinates.
  EuclideanIntegerPoint | A simple implementation of `Clusterable` for points with integer coordinates.
  KMeansPlusPlusClusterer<T extends Clusterable<T>> | Clustering algorithm based on David Arthur and Sergei Vassilvitski k-means++ algorithm.

- Enum Summary
  Enum | Description
  --- | ---
  DBSCANClusterer.PointStatus | Status of a point during the clustering process.
  KMeansPlusPlusClusterer.EmptyClusterStrategy | Strategies to use for replacing an empty cluster.

## Package org.apache.commons.math3.stat.clustering Description

Clustering algorithms

Copyright (c) 2003-2013 Apache Software Foundation