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

Class RandomlyGeneratedInitialMeans

java.lang.Object

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

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

All Implemented Interfaces:

KMeansInitialization<NumberVector>

public class RandomlyGeneratedInitialMeans
extends AbstractKMeansInitialization<NumberVector>

Initialize k-means by generating random vectors (within the data sets value range).

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	RandomlyGeneratedInitialMeans.Parameterizer 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
RandomlyGeneratedInitialMeans(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

Methods inherited from class java.lang.Object

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

Constructor Detail

RandomlyGeneratedInitialMeans

public RandomlyGeneratedInitialMeans(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

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