org.encog.ml.kmeans
Class KMeansClustering

java.lang.Object
  org.encog.ml.kmeans.KMeansClustering

All Implemented Interfaces:

MLClustering, MLMethod

public class KMeansClustering
extends Object
implements MLClustering

This class performs a basic K-Means clustering. This class can be used on either supervised or unsupervised data. For supervised data, the ideal values will be ignored. http://en.wikipedia.org/wiki/Kmeans

Constructor Summary

KMeansClustering(int theK, MLDataSet theSet)
Construct the K-Means object.

Method Summary

MLCluster[]	getClusters()
void	iteration() Perform a single training iteration.
void	iteration(int count) The number of iterations to perform.
int	numClusters()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

KMeansClustering

public KMeansClustering(int theK,
                        MLDataSet theSet)

Construct the K-Means object.

Parameters:

k - The number of clusters to use.

theSet - The dataset to cluster.

Method Detail

iteration

public final void iteration()

Perform a single training iteration.

Specified by:

iteration in interface MLClustering

iteration

public final void iteration(int count)

The number of iterations to perform.

Specified by:

iteration in interface MLClustering

Parameters:

count - The count of iterations.

getClusters

public MLCluster[] getClusters()

Specified by:

getClusters in interface MLClustering

Returns:

The clusters.

numClusters

public int numClusters()

Specified by:

numClusters in interface MLClustering

Returns:

The number of clusters.