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

Class RandomlyGeneratedInitialMeans<V extends NumberVector<V,?>>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.RandomlyGeneratedInitialMeans<V>

Type Parameters:

V - Vector type

All Implemented Interfaces:

KMeansInitialization<V>

public class RandomlyGeneratedInitialMeans<V extends NumberVector<V,?>>
extends AbstractKMeansInitialization<V>

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

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	RandomlyGeneratedInitialMeans.Parameterizer<V extends NumberVector<V,?>> Parameterization class.

Field Summary

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

seed

Constructor Summary

Constructors

Constructor and Description
RandomlyGeneratedInitialMeans(Long seed) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
List<V>	chooseInitialMeans(Relation<V> relation, int k, PrimitiveDistanceFunction<? super V,?> distanceFunction) 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(Long seed)

Constructor.

Parameters:

seed - Random seed.

Method Detail

chooseInitialMeans

public List<V> chooseInitialMeans(Relation<V> relation,
                         int k,
                         PrimitiveDistanceFunction<? super V,?> distanceFunction)

Description copied from interface: KMeansInitialization

Choose initial means

Parameters:

relation - Relation

k - Parameter k

distanceFunction - Distance function

Returns:

List of chosen means for k-means