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

Class FarthestSumPointsInitialMeans<O>

java.lang.Object

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

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

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

Type Parameters:

O - Object type for kmedoids and kmedians

All Implemented Interfaces:

KMeansInitialization<NumberVector>, KMedoidsInitialization<O>

public class FarthestSumPointsInitialMeans<O>
extends FarthestPointsInitialMeans<O>

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

Author:

Erich Schubert

Nested Class Summary

Nested Classes

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

Field Summary

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

dropfirst

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

rnd

Constructor Summary

Constructors

Constructor and Description
FarthestSumPointsInitialMeans(RandomFactory rnd, boolean dropfirst) 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

Constructor Detail

FarthestSumPointsInitialMeans

public FarthestSumPointsInitialMeans(RandomFactory rnd,
                             boolean dropfirst)

Constructor.

Parameters:

rnd - Random generator.

dropfirst - Flag to discard the first vector.

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>

Overrides:

chooseInitialMeans in class FarthestPointsInitialMeans<O>

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>

Overrides:

chooseInitialMedoids in class FarthestPointsInitialMeans<O>

Parameters:

k - Parameter k

ids - Candidate IDs.

distQ - Distance function

Returns:

List of chosen means for k-means