Class KMediansLloyd<V extends NumberVector>

  • Type Parameters:
    V - vector datatype
    All Implemented Interfaces:
    Algorithm, ClusteringAlgorithm<Clustering<MeanModel>>, KMeans<V,​MeanModel>

    @Reference(title="Clustering via Concave Minimization",
               authors="P. S. Bradley, O. L. Mangasarian, W. N. Street",
               booktitle="Advances in Neural Information Processing Systems",
               url="https://papers.nips.cc/paper/1260-clustering-via-concave-minimization",
               bibkey="DBLP:conf/nips/BradleyMS96")
    public class KMediansLloyd<V extends NumberVector>
    extends AbstractKMeans<V,​MeanModel>
    k-medians clustering algorithm, but using Lloyd-style bulk iterations instead of the more complicated approach suggested by Kaufman and Rousseeuw (see PAM instead).

    Reference:

    Clustering via Concave Minimization
    P. S. Bradley, O. L. Mangasarian, W. N. Street
    Advances in Neural Information Processing Systems (NIPS'96)

    Since:
    0.5.0
    Author:
    Erich Schubert
    • Field Detail

      • LOG

        private static final Logging LOG
        The logger for this class.
    • Constructor Detail

      • KMediansLloyd

        public KMediansLloyd​(NumberVectorDistance<? super V> distance,
                             int k,
                             int maxiter,
                             KMeansInitialization initializer)
        Constructor.
        Parameters:
        distance - distance function
        k - k parameter
        maxiter - Maxiter parameter
        initializer - Initialization method