Package elki.clustering.kmeans.initialization

Class Ostrovsky

java.lang.Object

elki.clustering.kmeans.initialization.AbstractKMeansInitialization

elki.clustering.kmeans.initialization.Ostrovsky

All Implemented Interfaces:

KMeansInitialization

@Reference(authors="R. Ostrovsky, Y. Rabani, L. J. Schulman, C. Swamy",title="The effectiveness of Lloyd-type methods for the k-means problem",booktitle="Symposium on Foundations of Computer Science (FOCS)",url="https://doi.org/10.1109/FOCS.2006.75",bibkey="DBLP:conf/focs/OstrovskyRSS06") @Reference(authors="R. Ostrovsky, Y. Rabani, L. J. Schulman, C. Swamy",title="The effectiveness of Lloyd-type methods for the k-means problem",booktitle="Journal of the ACM 59(6)",url="https://doi.org/10.1145/2395116.2395117",bibkey="DBLP:journals/jacm/OstrovskyRSS12")
public class Ostrovsky
extends AbstractKMeansInitialization

Ostrovsky initial means, a variant of k-means++ that is expected to give slightly better results on average, but only works for k-means and not for, e.g., PAM (k-medoids).

Reference:

R. Ostrovsky, Y. Rabani, L. J. Schulman, C. Swamy
The effectiveness of Lloyd-type methods for the k-means problem.
Symposium on Foundations of Computer Science (FOCS)

R. Ostrovsky, Y. Rabani, L. J. Schulman, C. Swamy
The effectiveness of Lloyd-type methods for the k-means problem.
Journal of the ACM 59(6)

Since:

0.7.5

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
protected class	Ostrovsky.NumberVectorInstance	Instance for number vectors.
static class	Ostrovsky.Par	Parameterization class.

Field Summary

Fields

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

Fields inherited from class elki.clustering.kmeans.initialization.AbstractKMeansInitialization

rnd

Constructor Summary

Constructors

Constructor	Description
Ostrovsky(RandomFactory rnd)	Constructor.

Method Summary

Modifier and Type	Method	Description
double[][]	chooseInitialMeans(Relation<? extends NumberVector> relation, int k, NumberVectorDistance<?> distance)	Choose initial means

Methods inherited from class elki.clustering.kmeans.initialization.AbstractKMeansInitialization

unboxVectors

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

Ostrovsky

public Ostrovsky(RandomFactory rnd)

Constructor.

Parameters:

rnd - Random generator.

Method Detail

chooseInitialMeans

public double[][] chooseInitialMeans(Relation<? extends NumberVector> relation,
                                     int k,
                                     NumberVectorDistance<?> distance)

Description copied from interface: KMeansInitialization

Choose initial means

Parameters:

relation - Relation

k - Parameter k

distance - Distance function

Returns:

List of chosen means for k-means