Class Ostrovsky
- java.lang.Object
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- elki.clustering.kmeans.initialization.AbstractKMeansInitialization
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- elki.clustering.kmeans.initialization.Ostrovsky
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- 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
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Nested Class Summary
Nested Classes Modifier and Type Class Description protected class
Ostrovsky.NumberVectorInstance
Instance for number vectors.static class
Ostrovsky.Par
Parameterization class.
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Field Summary
Fields Modifier and Type Field Description private static Logging
LOG
Class logger.-
Fields inherited from class elki.clustering.kmeans.initialization.AbstractKMeansInitialization
rnd
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Constructor Summary
Constructors Constructor Description Ostrovsky(RandomFactory rnd)
Constructor.
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Method Summary
All Methods Instance Methods Concrete Methods 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
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Field Detail
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LOG
private static final Logging LOG
Class logger.
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Constructor Detail
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Ostrovsky
public Ostrovsky(RandomFactory rnd)
Constructor.- Parameters:
rnd
- Random generator.
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Method Detail
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chooseInitialMeans
public double[][] chooseInitialMeans(Relation<? extends NumberVector> relation, int k, NumberVectorDistance<?> distance)
Description copied from interface:KMeansInitialization
Choose initial means- Parameters:
relation
- Relationk
- Parameter kdistance
- Distance function- Returns:
- List of chosen means for k-means
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