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

Class PAMInitialMeans<O>

java.lang.Object

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

Type Parameters:

O - Object type for KMedoids initialization

All Implemented Interfaces:

KMeansInitialization<NumberVector>, KMedoidsInitialization<O>

@Reference(title="Clustering my means of Medoids",
           authors="Kaufman, L. and Rousseeuw, P.J.",
           booktitle="Statistical Data Analysis Based on the L_1\u2013Norm and Related Methods")
public class PAMInitialMeans<O>
extends Object
implements KMeansInitialization<NumberVector>, KMedoidsInitialization<O>

PAM initialization for k-means (and of course, PAM). Reference:

Clustering my means of Medoids
Kaufman, L. and Rousseeuw, P.J.
in: Statistical Data Analysis Based on the L_1–Norm and Related Methods

Author:

Erich Schubert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
private static Logging	LOG Class logger.

Constructor Summary

Constructors

Constructor and Description
PAMInitialMeans() 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

Methods inherited from class java.lang.Object

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

Field Detail

LOG

private static final Logging LOG

Class logger.

Constructor Detail

PAMInitialMeans

public PAMInitialMeans()

Constructor.

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