Class SphericalSimplifiedHamerlyKMeans<V extends NumberVector>

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

    @Reference(authors="Erich Schubert, Andreas Lang, Gloria Feher",title="Accelerating Spherical k-Means",booktitle="Int. Conf. on Similarity Search and Applications, SISAP 2021",url="https://doi.org/10.1007/978-3-030-89657-7_17",bibkey="DBLP:conf/sisap/SchubertLF21") @Reference(authors="Erich Schubert",title="A Triangle Inequality for Cosine Similarity",booktitle="Int. Conf. on Similarity Search and Applications, SISAP 2021",url="https://doi.org/10.1007/978-3-030-89657-7_3",bibkey="DBLP:conf/sisap/Schubert21")
    public class SphericalSimplifiedHamerlyKMeans<V extends NumberVector>
    extends SphericalKMeans<V>
    A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality.

    FIXME: currently requires the vectors to be L2 normalized beforehand

    Reference:

    Erich Schubert, Andreas Lang, Gloria Feher
    Accelerating Spherical k-Means
    Int. Conf. on Similarity Search and Applications, SISAP 2021

    The underlying triangle inequality used for pruning is introduced in:

    Erich Schubert
    A Triangle Inequality for Cosine Similarity
    Int. Conf. on Similarity Search and Applications, SISAP 2021

    Since:
    0.8.0
    Author:
    Erich Schubert
    • Field Detail

      • LOG

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

        protected boolean varstat
        Flag whether to compute the final variance statistic.
    • Constructor Detail

      • SphericalSimplifiedHamerlyKMeans

        public SphericalSimplifiedHamerlyKMeans​(int k,
                                                int maxiter,
                                                KMeansInitialization initializer,
                                                boolean varstat)
        Constructor.
        Parameters:
        k - k parameter
        maxiter - Maxiter parameter
        initializer - Initialization method
        varstat - Compute the variance statistic