Package dev.brachtendorf.clustering

Class KMeansPlusPlus

java.lang.Object

dev.brachtendorf.clustering.KMeans

dev.brachtendorf.clustering.KMeansPlusPlus

All Implemented Interfaces:

ClusterAlgorithm

public class KMeansPlusPlus
extends KMeans

Author:

Kilian

Field Summary

Fields inherited from class dev.brachtendorf.clustering.KMeans

distanceFunction, k, lastIterationCount

Constructor Summary

Constructors

Constructor	Description
KMeansPlusPlus(int clusters)	Create a KMeans clusterer with k clusters and EuclideanDistance.
KMeansPlusPlus(int clusters, DistanceFunction distanceFunction)	Create a KMeans clusterer

Method Summary

Modifier and Type	Method	Description
protected DoubleSummaryStatistics[][]	computeStartingClusters(double[][] data, int k, int dataDimension)

Methods inherited from class dev.brachtendorf.clustering.KMeans

cluster, computeKMeans, iterations

Methods inherited from class java.lang.Object

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

Constructor Detail

KMeansPlusPlus

public KMeansPlusPlus(int clusters)

Create a KMeans clusterer with k clusters and EuclideanDistance.

Parameters:

clusters - the number of cluster to partition the data into

KMeansPlusPlus

public KMeansPlusPlus(int clusters,
                      DistanceFunction distanceFunction)

Create a KMeans clusterer

Parameters:

clusters - the number of cluster to partition the data into

distanceFunction - the distanceFunction used to compute the distance between data points

Method Detail

computeStartingClusters

protected DoubleSummaryStatistics[][] computeStartingClusters(double[][] data,
                                                              int k,
                                                              int dataDimension)

Overrides:

computeStartingClusters in class KMeans