Class 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
    • 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