Package elki.clustering.kmedoids

Class ReynoldsPAM<O>

java.lang.Object

elki.clustering.kmedoids.PAM<O>

elki.clustering.kmedoids.ReynoldsPAM<O>

Type Parameters:

O - vector datatype

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<MedoidModel>>, KMedoidsClustering<O>

@Reference(authors="A. P. Reynolds, G. Richards, B. de la Iglesia, V. J. Rayward-Smith",
           title="Clustering Rules: A Comparison of Partitioning and Hierarchical Clustering Algorithms",
           booktitle="J. Math. Model. Algorithms 5(4)",
           url="https://doi.org/10.1007/s10852-005-9022-1",
           bibkey="DBLP:journals/jmma/ReynoldsRIR06")
public class ReynoldsPAM<O>
extends PAM<O>

The Partitioning Around Medoids (PAM) algorithm with some additional optimizations proposed by Reynolds et al.

In our implementation, we could not observe a substantial improvement over the original PAM algorithm. This may be because of modern CPU architectures, where saving an addition may be neglibile compared to caching and pipelining.

Reference:

A. P. Reynolds, G. Richards, B. de la Iglesia, V. J. Rayward-Smith
Clustering Rules: A Comparison of Partitioning and Hierarchical Clustering Algorithms
J. Math. Model. Algorithms 5(4)

Since:

0.5.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
protected static class	ReynoldsPAM.Instance	Instance for a single dataset.
static class	ReynoldsPAM.Par<V>	Parameterization class.

Nested classes/interfaces inherited from interface elki.Algorithm

Algorithm.Utils

Field Summary

Fields

Modifier and Type	Field	Description
private static java.lang.String	KEY	Key for statistics logging.
private static Logging	LOG	The logger for this class.

Fields inherited from class elki.clustering.kmedoids.PAM

distance, initializer, k, maxiter

Constructor Summary

Constructors

Constructor	Description
ReynoldsPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)	Constructor.

Method Summary

Modifier and Type	Method	Description
protected Logging	getLogger()	Get the static class logger.
Clustering<MedoidModel>	run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)	Run k-medoids clustering with a given distance query. Not a very elegant API, but needed for some types of nested k-medoids.

Methods inherited from class elki.clustering.kmedoids.PAM

getInputTypeRestriction, initialMedoids, run, wrapResult

Methods inherited from class java.lang.Object

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

Methods inherited from interface elki.clustering.ClusteringAlgorithm

autorun

Field Detail

LOG

private static final Logging LOG

The logger for this class.

KEY

private static final java.lang.String KEY

Key for statistics logging.

Constructor Detail

ReynoldsPAM

public ReynoldsPAM(Distance<? super O> distance,
                   int k,
                   int maxiter,
                   KMedoidsInitialization<O> initializer)

Constructor.

Parameters:

distance - distance function

k - k parameter

maxiter - Maxiter parameter

initializer - Function to generate the initial means

Method Detail

run

public Clustering<MedoidModel> run(Relation<O> relation,
                                   int k,
                                   DistanceQuery<? super O> distQ)

Description copied from interface: KMedoidsClustering

Run k-medoids clustering with a given distance query.
Not a very elegant API, but needed for some types of nested k-medoids.

Specified by:

run in interface KMedoidsClustering<O>

Overrides:

run in class PAM<O>

Parameters:

relation - relation to use

k - Number of clusters

distQ - Distance query to use

Returns:

result

getLogger

protected Logging getLogger()

Description copied from class: PAM

Get the static class logger.

Overrides:

getLogger in class PAM<O>