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

Class FirstKInitialMeans<O>

java.lang.Object

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

Type Parameters:

O - Object type for KMedoids

All Implemented Interfaces:

KMeansInitialization<NumberVector>, KMedoidsInitialization<O>

public class FirstKInitialMeans<O>
extends Object
implements KMeansInitialization<NumberVector>, KMedoidsInitialization<O>

Initialize K-means by using the first k objects as initial means.

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	FirstKInitialMeans.Parameterizer<V extends NumberVector> Parameterization class.

Constructor Summary

Constructors

Constructor and Description
FirstKInitialMeans() 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> distanceFunction) Choose initial means

Methods inherited from class java.lang.Object

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

Constructor Detail

FirstKInitialMeans

public FirstKInitialMeans()

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> distanceFunction)

Description copied from interface: KMedoidsInitialization

Choose initial means

Specified by:

chooseInitialMedoids in interface KMedoidsInitialization<O>

Parameters:

k - Parameter k

ids - Candidate IDs.

distanceFunction - Distance function

Returns:

List of chosen means for k-means