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

Class FastCLARANS<V>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<R>

de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<V,Clustering<MedoidModel>>

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

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

Type Parameters:

V - Vector type

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<MedoidModel>>, DistanceBasedAlgorithm<V>

@Reference(authors="Erich Schubert, Peter J. Rousseeuw",
           title="Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms",
           booktitle="preprint, to appear",
           url="https://arxiv.org/abs/1810.05691",
           bibkey="DBLP:journals/corr/abs-1810-05691")
 @Priority(value=101)
public class FastCLARANS<V>
extends CLARANS<V>

A faster variation of CLARANS, that can explore O(k) as many swaps at a similar cost by considering all medoids for each candidate non-medoid. Since this means sampling fewer non-medoids, we suggest to increase the subsampling rate slightly to get higher quality than CLARANS, at better runtime.

Reference:

Erich Schubert, Peter J. Rousseeuw
Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms
preprint, to appear

Since:

0.7.5

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
protected static class	FastCLARANS.Assignment Assignment state.
static class	FastCLARANS.Parameterizer<V> Parameterization class.

Field Summary

Fields

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

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

k, maxneighbor, numlocal, random

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

ALGORITHM_ID

Fields inherited from interface de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
FastCLARANS(DistanceFunction<? super V> distanceFunction, int k, int numlocal, double maxneighbor, RandomFactory random) Constructor.

Method Summary

Modifier and Type	Method and Description
protected Logging	getLogger() Get the (STATIC) logger for this class.
Clustering<MedoidModel>	run(Database database, Relation<V> relation)

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARANS

getInputTypeRestriction

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm

getDistanceFunction

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

run

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.clustering.ClusteringAlgorithm

run

Field Detail

LOG

private static final Logging LOG

Class logger.

Constructor Detail

FastCLARANS

public FastCLARANS(DistanceFunction<? super V> distanceFunction,
                   int k,
                   int numlocal,
                   double maxneighbor,
                   RandomFactory random)

Constructor.

Parameters:

distanceFunction - Distance function to use

k - Number of clusters to produce

numlocal - Number of samples (restarts)

maxneighbor - Neighbor sampling rate (absolute or relative)

random - Random generator

Method Detail

run

public Clustering<MedoidModel> run(Database database,
                                   Relation<V> relation)

Overrides:

run in class CLARANS<V>

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Overrides:

getLogger in class CLARANS<V>

Returns:

the static logger