MultiKMeansPlusPlusClusterer (Commons Math 3.2 API)

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org.apache.commons.math3.ml.clustering
Class MultiKMeansPlusPlusClusterer<T extends Clusterable>

java.lang.Object
  org.apache.commons.math3.ml.clustering.Clusterer<T>
      org.apache.commons.math3.ml.clustering.MultiKMeansPlusPlusClusterer<T>


Type Parameters:: T - type of the points to cluster

public class MultiKMeansPlusPlusClusterer<T extends Clusterable>
extends Clusterer<T>
extends Clusterer<T>

A wrapper around a k-means++ clustering algorithm which performs multiple trials and returns the best solution.

Since:: 3.2
Version:: $Id: MultiKMeansPlusPlusClusterer.java 1462375 2013-03-29 01:42:42Z psteitz $

Constructor Summary
`MultiKMeansPlusPlusClusterer(KMeansPlusPlusClusterer<T> clusterer, int numTrials)` Build a clusterer.

Method Summary
`List<CentroidCluster<T>>`	`cluster(Collection<T> points)` Runs the K-means++ clustering algorithm.
`KMeansPlusPlusClusterer<T>`	`getClusterer()` Returns the embedded k-means clusterer used by this instance.
`int`	`getNumTrials()` Returns the number of trials this instance will do.

Methods inherited from class org.apache.commons.math3.ml.clustering.Clusterer
`distance, getDistanceMeasure`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

MultiKMeansPlusPlusClusterer

public MultiKMeansPlusPlusClusterer(KMeansPlusPlusClusterer<T> clusterer,
                                    int numTrials)

Build a clusterer.

Parameters:: clusterer - the k-means clusterer to use; numTrials - number of trial runs

Method Detail

getClusterer

public KMeansPlusPlusClusterer<T> getClusterer()

Returns the embedded k-means clusterer used by this instance.

Returns:: the embedded clusterer

getNumTrials

public int getNumTrials()

Returns the number of trials this instance will do.

Returns:: the number of trials

cluster

public List<CentroidCluster<T>> cluster(Collection<T> points)
                                                     throws MathIllegalArgumentException,
                                                            ConvergenceException

Runs the K-means++ clustering algorithm.

Specified by:: cluster in class Clusterer<T extends Clusterable>

Parameters:: points - the points to cluster
Returns:: a list of clusters containing the points
Throws:: MathIllegalArgumentException - if the data points are null or the number of clusters is larger than the number of data points; ConvergenceException - if an empty cluster is encountered and the underlying KMeansPlusPlusClusterer has its KMeansPlusPlusClusterer.EmptyClusterStrategy is set to ERROR.