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

Class RandomlyChosenInitialMeans<O>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.AbstractKMeansInitialization<NumberVector>

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.RandomlyChosenInitialMeans<O>

Type Parameters:

O - Vector type

All Implemented Interfaces:

KMeansInitialization<NumberVector>, KMedoidsInitialization<O>

@Reference(authors="E. W. Forgy",
           title="Cluster analysis of multivariate data: efficiency versus interpretability of classifications",
           booktitle="Biometrics 21(3)")
public class RandomlyChosenInitialMeans<O>
extends AbstractKMeansInitialization<NumberVector>
implements KMedoidsInitialization<O>

Initialize K-means by randomly choosing k existing elements as cluster centers. This initialization is attributed to:

E. W. Forgy
Cluster analysis of multivariate data : efficiency versus interpretability of classifications
Abstract published in Biometrics 21(3)

but we were unable to verify this so far (apparently, only an abstract is available in Biometrics).

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	RandomlyChosenInitialMeans.Parameterizer<V> Parameterization class.

Field Summary

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

rnd

Constructor Summary

Constructors

Constructor and Description
RandomlyChosenInitialMeans(RandomFactory rnd) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
<T extends NumberVector,V extends NumberVector> List<V>	chooseInitialMeans(Database database, Relation<T> relation, int k, NumberVectorDistanceFunction<? super T> distanceFunction, NumberVector.Factory<V> factory) Choose initial means
DBIDs	chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distanceFunction) Choose initial means

Methods inherited from class java.lang.Object

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

Constructor Detail

RandomlyChosenInitialMeans

public RandomlyChosenInitialMeans(RandomFactory rnd)

Constructor.

Parameters:

rnd - Random generator.

Method Detail

chooseInitialMeans

public <T extends NumberVector,V extends NumberVector> List<V> chooseInitialMeans(Database database,
                                                                         Relation<T> relation,
                                                                         int k,
                                                                         NumberVectorDistanceFunction<? super T> distanceFunction,
                                                                         NumberVector.Factory<V> factory)

Description copied from interface: KMeansInitialization

Choose initial means

Specified by:

chooseInitialMeans in interface KMeansInitialization<NumberVector>

Type Parameters:

T - Input vector type

V - Output vector type

Parameters:

database - Database context

relation - Relation

k - Parameter k

distanceFunction - Distance function

factory - Factory for output vectors.

Returns:

List of chosen means for k-means

chooseInitialMedoids

public DBIDs chooseInitialMedoids(int k,
                         DBIDs ids,
                         DistanceQuery<? super O> distanceFunction)

Description copied from interface: KMedoidsInitialization

Choose initial means

Specified by:

chooseInitialMedoids in interface KMedoidsInitialization<O>

Parameters:

k - Parameter k

ids - Candidate IDs.

distanceFunction - Distance function

Returns:

List of chosen means for k-means