Package elki.clustering.kmeans

Class CompareMeans<V extends NumberVector>

java.lang.Object

elki.clustering.kmeans.AbstractKMeans<V,KMeansModel>

elki.clustering.kmeans.CompareMeans<V>

Type Parameters:

V - vector datatype

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<KMeansModel>>, KMeans<V,KMeansModel>

Direct Known Subclasses:

SortMeans

@Title("Compare-Means")
@Reference(authors="S. J. Phillips",
           title="Acceleration of k-means and related clustering algorithms",
           booktitle="Proc. 4th Int. Workshop on Algorithm Engineering and Experiments (ALENEX 2002)",
           url="https://doi.org/10.1007/3-540-45643-0_13",
           bibkey="DBLP:conf/alenex/Phillips02")
public class CompareMeans<V extends NumberVector>
extends AbstractKMeans<V,KMeansModel>

Compare-Means: Accelerated k-means by exploiting the triangle inequality and pairwise distances of means to prune candidate means.

Reference:

S. J. Phillips
Acceleration of k-means and related clustering algorithms
Proc. 4th Int. W. on Algorithm Engineering and Experiments (ALENEX 2002)

Since:

0.7.1

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
protected static class	CompareMeans.Instance	Inner instance, storing state for a single data set.
static class	CompareMeans.Par<V extends NumberVector>	Parameterization class.

Nested classes/interfaces inherited from interface elki.Algorithm

Algorithm.Utils

Field Summary

Fields

Modifier and Type	Field	Description
private static Logging	LOG	The logger for this class.

Fields inherited from class elki.clustering.kmeans.AbstractKMeans

distance, initializer, k, maxiter

Fields inherited from interface elki.clustering.kmeans.KMeans

DISTANCE_FUNCTION_ID, INIT_ID, K_ID, MAXITER_ID, SEED_ID, VARSTAT_ID

Constructor Summary

Constructors

Constructor	Description
CompareMeans(NumberVectorDistance<? super V> distance, int k, int maxiter, KMeansInitialization initializer)	Constructor.

Method Summary

Modifier and Type	Method	Description
protected Logging	getLogger()	Get the (STATIC) logger for this class.
Clustering<KMeansModel>	run(Relation<V> relation)	Run the clustering algorithm.

Methods inherited from class elki.clustering.kmeans.AbstractKMeans

getDistance, getInputTypeRestriction, incrementalUpdateMean, initialMeans, means, minusEquals, nearestMeans, plusEquals, plusMinusEquals, setDistance, setInitializer, setK

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.

Constructor Detail

CompareMeans

public CompareMeans(NumberVectorDistance<? super V> distance,
                    int k,
                    int maxiter,
                    KMeansInitialization initializer)

Constructor.

Parameters:

distance - distance function

k - k parameter

maxiter - Maxiter parameter

initializer - Initialization method

Method Detail

run

public Clustering<KMeansModel> run(Relation<V> relation)

Description copied from interface: KMeans

Run the clustering algorithm.

Parameters:

relation - Relation to process.

Returns:

Clustering result

getLogger

protected Logging getLogger()

Description copied from class: AbstractKMeans

Get the (STATIC) logger for this class.

Specified by:

getLogger in class AbstractKMeans<V extends NumberVector,KMeansModel>

Returns:

the static logger