Package elki.clustering.kmedoids.initialization

Class ParkJun<O>

java.lang.Object

elki.clustering.kmedoids.initialization.ParkJun<O>

Type Parameters:

O - Object type for KMedoids initialization

All Implemented Interfaces:

KMeansInitialization, KMedoidsInitialization<O>

@Priority(-100)
@Reference(authors="H.-S. Park, C.-H. Jun",
           title="A simple and fast algorithm for K-medoids clustering",
           booktitle="Expert Systems with Applications 36(2)",
           url="https://doi.org/10.1016/j.eswa.2008.01.039",
           bibkey="DBLP:journals/eswa/ParkJ09")
public class ParkJun<O>
extends java.lang.Object
implements KMeansInitialization, KMedoidsInitialization<O>

Initialization method proposed by Park and Jun.

It is easy to imagine that this approach can become problematic, because it does not take the distances between medoids into account. In the worst case, it may choose k duplicates as initial centers, therefore we cannot recommend this strategy, but it is provided for completeness.

Reference:

H.-S. Park, C.-H. Jun
A simple and fast algorithm for K-medoids clustering
Expert Systems with Applications 36(2)

Since:

0.7.5

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	ParkJun.Par<V>	Parameterization class.

Field Summary

Fields

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

Constructor Summary

Constructors

Constructor	Description
ParkJun()	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 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

ParkJun

public ParkJun()

Constructor.

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