Package elki.clustering.kmeans.initialization

Class FarthestPoints<O>

java.lang.Object

elki.clustering.kmeans.initialization.AbstractKMeansInitialization

elki.clustering.kmeans.initialization.FarthestPoints<O>

Type Parameters:

O - Object type for kMedoids and kMedians

All Implemented Interfaces:

KMeansInitialization, KMedoidsInitialization<O>

Direct Known Subclasses:

FarthestSumPoints

public class FarthestPoints<O>
extends AbstractKMeansInitialization
implements KMedoidsInitialization<O>

K-Means initialization by repeatedly choosing the farthest point (by the minimum distance to earlier points).

Note: this is less random than other initializations, so running multiple times will be more likely to return the same local minima.

Since:

0.6.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	FarthestPoints.Par<O>	Parameterization class.

Field Summary

Fields

Modifier and Type	Field	Description
(package private) boolean	dropfirst	Discard the first vector.

Fields inherited from class elki.clustering.kmeans.initialization.AbstractKMeansInitialization

rnd

Constructor Summary

Constructors

Constructor	Description
FarthestPoints(RandomFactory rnd, boolean dropfirst)	Constructor.

Method Summary

Modifier and Type	Method	Description
double[][]	chooseInitialMeans(Relation<? extends NumberVector> relation, int k, NumberVectorDistance<?> distance)	Choose initial means
DBIDs	chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)	Choose initial means

Methods inherited from class elki.clustering.kmeans.initialization.AbstractKMeansInitialization

unboxVectors

Methods inherited from class java.lang.Object

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

Field Detail

dropfirst

boolean dropfirst

Discard the first vector.

Constructor Detail

FarthestPoints

public FarthestPoints(RandomFactory rnd,
                      boolean dropfirst)

Constructor.

Parameters:

rnd - Random generator.

dropfirst - Flag to discard the first vector.

Method Detail

chooseInitialMeans

public double[][] chooseInitialMeans(Relation<? extends NumberVector> relation,
                                     int k,
                                     NumberVectorDistance<?> distance)

Description copied from interface: KMeansInitialization

Choose initial means

Specified by:

chooseInitialMeans in interface KMeansInitialization

Parameters:

relation - Relation

k - Parameter k

distance - Distance function

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