de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization

Class PredefinedInitialMeans

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.AbstractKMeansInitialization

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.PredefinedInitialMeans

All Implemented Interfaces:

KMeansInitialization

public class PredefinedInitialMeans
extends AbstractKMeansInitialization

Run k-means with prespecified initial means.

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	PredefinedInitialMeans.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
(package private) double[][]	initialMeans Initial means to return.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.AbstractKMeansInitialization

rnd

Constructor Summary

Constructors

Constructor and Description
PredefinedInitialMeans(double[][] initialMeans) Constructor.

Method Summary

Modifier and Type	Method and Description
double[][]	chooseInitialMeans(Database database, Relation<? extends NumberVector> relation, int k, NumberVectorDistanceFunction<?> distanceFunction) Choose initial means
void	setInitialClusters(java.util.List<? extends Cluster<? extends MeanModel>> initialMeans) Set the initial means.
void	setInitialMeans(double[][] initialMeans) Set the initial means.
void	setInitialMeans(java.util.List<double[]> initialMeans) Set the initial means.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.AbstractKMeansInitialization

unboxVectors

Methods inherited from class java.lang.Object

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

Field Detail

initialMeans

double[][] initialMeans

Initial means to return.

Constructor Detail

PredefinedInitialMeans

public PredefinedInitialMeans(double[][] initialMeans)

Constructor.

Parameters:

initialMeans - Initial means

Method Detail

setInitialMeans

public void setInitialMeans(java.util.List<double[]> initialMeans)

Set the initial means. Important notice: Use with care - the means are not copied!

Parameters:

initialMeans - initial means.

setInitialClusters

public void setInitialClusters(java.util.List<? extends Cluster<? extends MeanModel>> initialMeans)

Set the initial means. Important notice: Use with care - the means are not copied!

Parameters:

initialMeans - initial means.

setInitialMeans

public void setInitialMeans(double[][] initialMeans)

Set the initial means. Important notice: Use with care - the means are not copied!

Parameters:

initialMeans - initial means.

chooseInitialMeans

public double[][] chooseInitialMeans(Database database,
                                     Relation<? extends NumberVector> relation,
                                     int k,
                                     NumberVectorDistanceFunction<?> distanceFunction)

Description copied from interface: KMeansInitialization

Choose initial means

Parameters:

database - Database context

relation - Relation

k - Parameter k

distanceFunction - Distance function

Returns:

List of chosen means for k-means