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

Class KMeansPlusPlusInitialMeans<O>

java.lang.Object

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

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

Type Parameters:

O - Vector type

All Implemented Interfaces:

KMeansInitialization<NumberVector>, KMedoidsInitialization<O>

@Reference(authors="D. Arthur, S. Vassilvitskii",
           title="k-means++: the advantages of careful seeding",
           booktitle="Proc. of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2007",
           url="http://dx.doi.org/10.1145/1283383.1283494")
public class KMeansPlusPlusInitialMeans<O>
extends AbstractKMeansInitialization<NumberVector>
implements KMedoidsInitialization<O>

K-Means++ initialization for k-means. Reference:

D. Arthur, S. Vassilvitskii
k-means++: the advantages of careful seeding
In: Proc. of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2007

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	KMeansPlusPlusInitialMeans.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
KMeansPlusPlusInitialMeans(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> distQ) Choose initial means
protected <T> double	initialWeights(WritableDoubleDataStore weights, DBIDs ids, T latest, DistanceQuery<? super T> distQ) Initialize the weight list.
protected <T> double	updateWeights(WritableDoubleDataStore weights, DBIDs ids, T latest, DistanceQuery<? super T> distQ) Update the weight list.

Methods inherited from class java.lang.Object

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

Constructor Detail

KMeansPlusPlusInitialMeans

public KMeansPlusPlusInitialMeans(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> distQ)

Description copied from interface: KMedoidsInitialization

Choose initial means

Specified by:

chooseInitialMedoids in interface KMedoidsInitialization<O>

Parameters:

k - Parameter k

ids - Candidate IDs.

distQ - Distance function

Returns:

List of chosen means for k-means

initialWeights

protected <T> double initialWeights(WritableDoubleDataStore weights,
                        DBIDs ids,
                        T latest,
                        DistanceQuery<? super T> distQ)

Initialize the weight list.

Type Parameters:

T - Object type

Parameters:

weights - Weight list

ids - IDs

latest - Added ID

distQ - Distance query

Returns:

Weight sum

updateWeights

protected <T> double updateWeights(WritableDoubleDataStore weights,
                       DBIDs ids,
                       T latest,
                       DistanceQuery<? super T> distQ)

Update the weight list.

Type Parameters:

T - Object type

Parameters:

weights - Weight list

ids - IDs

latest - Added ID

distQ - Distance query

Returns:

Weight sum