Class InterclusterWeight

  • All Implemented Interfaces:
    CFInitWeight

    @Reference(authors="Andreas Lang and Erich Schubert",
               title="BETULA: Fast Clustering of Large Data with Improved BIRCH CF-Trees",
               booktitle="Information Systems",
               url="https://doi.org/10.1016/j.is.2021.101918",
               bibkey="DBLP:journals/is/LangS22")
    public class InterclusterWeight
    extends java.lang.Object
    implements CFInitWeight
    Initialization via n2 * D2²(cf1, cf2), which supposedly is closes to the idea of k-means++ initialization.

    References:

    Andreas Lang and Erich Schubert
    BETULA: Fast Clustering of Large Data with Improved BIRCH CF-Trees
    Information Systems

    Since:
    0.8.0
    Author:
    Andreas Lang
    • Constructor Detail

      • InterclusterWeight

        public InterclusterWeight()
    • Method Detail

      • squaredWeight

        public double squaredWeight​(ClusterFeature existing,
                                    ClusterFeature candidate)
        Description copied from interface: CFInitWeight
        Distance between two clustering features.
        Specified by:
        squaredWeight in interface CFInitWeight
        Parameters:
        existing - Previously chosen clustering feature
        candidate - Candidate clustering feature
        Returns:
        Weight