marytts.machinelearning
Class KMeansClusteringTrainerParams
java.lang.Object
marytts.machinelearning.KMeansClusteringTrainerParams
public class KMeansClusteringTrainerParams
- extends java.lang.Object
Wrapper class for K-Means clustering training parameters
- Author:
- Oytun Türk
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
KMEANS_MAX_ITERATIONS_DEFAULT
public static final int KMEANS_MAX_ITERATIONS_DEFAULT
- See Also:
- Constant Field Values
KMEANS_MIN_CLUSTER_CHANGE_PERCENT_DEFAULT
public static final double KMEANS_MIN_CLUSTER_CHANGE_PERCENT_DEFAULT
- See Also:
- Constant Field Values
KMEANS_IS_DIAGONAL_COVARIANCE_DEFAULT
public static final boolean KMEANS_IS_DIAGONAL_COVARIANCE_DEFAULT
- See Also:
- Constant Field Values
KMEANS_MIN_SAMPLES_IN_ONE_CLUSTER_DEFAULT
public static final int KMEANS_MIN_SAMPLES_IN_ONE_CLUSTER_DEFAULT
- See Also:
- Constant Field Values
numClusters
public int numClusters
maxIterations
public int maxIterations
minClusterChangePercent
public double minClusterChangePercent
isDiagonalOutputCovariance
public boolean isDiagonalOutputCovariance
minSamplesInOneCluster
public int minSamplesInOneCluster
minCovarianceAllowed
public double minCovarianceAllowed
globalVariances
public double[] globalVariances
KMeansClusteringTrainerParams
public KMeansClusteringTrainerParams()
KMeansClusteringTrainerParams
public KMeansClusteringTrainerParams(GMMTrainerParams gmmParams)
KMeansClusteringTrainerParams
public KMeansClusteringTrainerParams(KMeansClusteringTrainerParams existing)
setGlobalVariances
public void setGlobalVariances(double[] globalVariancesIn)