Class RadiusDistance

  • All Implemented Interfaces:
    CFDistance

    @Alias("R")
    @Reference(authors="Andreas Lang and Erich Schubert",title="BETULA: Numerically Stable CF-Trees for BIRCH Clustering",booktitle="Int. Conf on Similarity Search and Applications",url="https://doi.org/10.1007/978-3-030-60936-8_22",bibkey="DBLP:conf/sisap/LangS20") @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 RadiusDistance
    extends java.lang.Object
    implements CFDistance
    Average Radius (R) criterion.

    References:

    Andreas Lang and Erich Schubert
    BETULA: Numerically Stable CF-Trees for BIRCH Clustering
    Int. Conf on Similarity Search and Applications 2020

    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, Erich Schubert
    • Field Detail

    • Constructor Detail

      • RadiusDistance

        public RadiusDistance()
    • Method Detail

      • squaredDistance

        public double squaredDistance​(NumberVector nv,
                                      ClusterFeature cf1)
        Description copied from interface: CFDistance
        Distance of a vector to a clustering feature.
        Specified by:
        squaredDistance in interface CFDistance
        Parameters:
        nv - Vector
        cf1 - Clustering Feature
        Returns:
        Distance
      • squaredDistance

        public double squaredDistance​(ClusterFeature cf1,
                                      ClusterFeature cf2)
        Description copied from interface: CFDistance
        Distance between two clustering features.
        Specified by:
        squaredDistance in interface CFDistance
        Parameters:
        cf1 - First clustering feature
        cf2 - Second clustering feature
        Returns:
        Distance
      • matSelfInit

        public double matSelfInit​(ClusterFeature cf)
        Description copied from interface: CFDistance
        Initialization for self measure for new Combinatorial clustering Methods (Podani 1989)
        Specified by:
        matSelfInit in interface CFDistance
        Parameters:
        cf - Clustering Feature
        Returns:
        internal measure