org.openimaj.ml.clustering.kmeans.fast
Class FastShortKMeansInit

java.lang.Object
  org.openimaj.ml.clustering.kmeans.fast.FastShortKMeansInit

Direct Known Subclasses:

FastShortKMeansInit.RANDOM

public abstract class FastShortKMeansInit
extends Object

Author:

Jonathon Hare , Sina Samangooei Given a data source of samples and a set of clusters to fill, implementations of this class should initialise the KMeans algorithm. A default RANDOM implementation is provided which uses DataSource.getRandomRows(DATATYPE[])

Nested Class Summary

static class

FastShortKMeansInit.RANDOM

Constructor Summary

FastShortKMeansInit()

Method Summary

abstract void

initFastKMeans(DataSource<short[]> bds, short[][] clusters)

Methods inherited from class java.lang.Object

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

Constructor Detail

FastShortKMeansInit

public FastShortKMeansInit()

Method Detail

initFastKMeans

public abstract void initFastKMeans(DataSource<short[]> bds,
                                    short[][] clusters)
                             throws IOException

Parameters:

bds - the data source of samples

clusters - the clusters to init

Throws:

IOException - problem reading samples