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

Class FarthestPointsInitialMeans<V,D extends NumberDistance<D,?>>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.FarthestPointsInitialMeans<V,D>

Type Parameters:

V - Vector type

D - Distance type

All Implemented Interfaces:

KMeansInitialization<V>, KMedoidsInitialization<V>

public class FarthestPointsInitialMeans<V,D extends NumberDistance<D,?>>
extends AbstractKMeansInitialization<V>
implements KMedoidsInitialization<V>

K-Means initialization by repeatedly choosing the farthest point. Note: this is less random than other initializations, so running multiple times will be more likely to return the same local minima.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	FarthestPointsInitialMeans.Parameterizer<V,D extends NumberDistance<D,?>> Parameterization class.

Field Summary

Fields

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

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

rnd

Constructor Summary

Constructors

Constructor and Description
FarthestPointsInitialMeans(RandomFactory rnd, boolean dropfirst) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
List<V>	chooseInitialMeans(Database database, Relation<V> relation, int k, PrimitiveDistanceFunction<? super NumberVector<?>,?> distanceFunction) Choose initial means
DBIDs	chooseInitialMedoids(int k, DistanceQuery<? super V,?> distQ2) Choose initial means

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

FarthestPointsInitialMeans

public FarthestPointsInitialMeans(RandomFactory rnd,
                          boolean dropfirst)

Constructor.

Parameters:

rnd - Random generator.

dropfirst - Flag to discard the first vector.

Method Detail

chooseInitialMeans

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

Description copied from interface: KMeansInitialization

Choose initial means

Specified by:

chooseInitialMeans in interface KMeansInitialization<V>

Parameters:

database - Database context

relation - Relation

k - Parameter k

distanceFunction - Distance function

Returns:

List of chosen means for k-means

chooseInitialMedoids

public DBIDs chooseInitialMedoids(int k,
                         DistanceQuery<? super V,?> distQ2)

Description copied from interface: KMedoidsInitialization

Choose initial means

Specified by:

chooseInitialMedoids in interface KMedoidsInitialization<V>

Parameters:

k - Parameter k

distQ2 - Distance function

Returns:

List of chosen means for k-means