marytts.machinelearning
Class KMeansClusteringTrainer

java.lang.Object
  marytts.machinelearning.KMeansClusteringTrainer

public class KMeansClusteringTrainer
extends java.lang.Object

K-Means clustering training algorithm Reference: J. MacQueen, 1967, "Some methods for classification and analysis of multivariate observations", Proc. Fifth Berkeley Symp. on Math. Statist. and Prob., Vol. 1 (Univ. of Calif. Press, 1967), pp. 281-297.

Author:

Oytun Türk

Field Summary

int[]	clusterIndices
Cluster[]	clusters
double[][]	covMatrixGlobal
double[][]	invCovMatrixGlobal
int[]	totalObservationsInClusters

Constructor Summary

KMeansClusteringTrainer()

Method Summary

int	getFeatureDimension()
int	getTotalClusters()
boolean	isDiagonalCovariance()
void	train(double[][] x, KMeansClusteringTrainerParams kmeansParams)

Methods inherited from class java.lang.Object

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

Field Detail

clusters

public Cluster[] clusters

totalObservationsInClusters

public int[] totalObservationsInClusters

clusterIndices

public int[] clusterIndices

covMatrixGlobal

public double[][] covMatrixGlobal

invCovMatrixGlobal

public double[][] invCovMatrixGlobal

Constructor Detail

KMeansClusteringTrainer

public KMeansClusteringTrainer()

Method Detail

train

public void train(double[][] x,
                  KMeansClusteringTrainerParams kmeansParams)

getFeatureDimension

public int getFeatureDimension()

getTotalClusters

public int getTotalClusters()

isDiagonalCovariance

public boolean isDiagonalCovariance()