org.openimaj.ml.clustering.kmeans

Class FeatureVectorKMeansInit.RANDOM<T>

java.lang.Object

org.openimaj.ml.clustering.kmeans.FeatureVectorKMeansInit<T>

org.openimaj.ml.clustering.kmeans.FeatureVectorKMeansInit.RANDOM<T>

Type Parameters:

T - Type of object being clustered

Enclosing class:

FeatureVectorKMeansInit<T>

public static class FeatureVectorKMeansInit.RANDOM<T>
extends FeatureVectorKMeansInit<T>

Simple kmeans initialized on randomly selected samples.

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk), Sina Samangooei (ss@ecs.soton.ac.uk)

Nested Class Summary

Nested classes/interfaces inherited from class org.openimaj.ml.clustering.kmeans.FeatureVectorKMeansInit

FeatureVectorKMeansInit.RANDOM<T>

Constructor Summary

Constructors

Constructor and Description
RANDOM()

Method Summary

Modifier and Type	Method and Description
void	initKMeans(DataSource<T> bds, T[] clusters) Initialise the centroids based on the given data.

Methods inherited from class java.lang.Object

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

Constructor Detail

RANDOM

public RANDOM()

Method Detail

initKMeans

public void initKMeans(DataSource<T> bds,
                       T[] clusters)
                throws IOException

Description copied from class: FeatureVectorKMeansInit

Initialise the centroids based on the given data.

Specified by:

initKMeans in class FeatureVectorKMeansInit<T>

Parameters:

bds - the data source of samples

clusters - the clusters to init

Throws:

IOException - problem reading samples