Class WardLinkage


  • public class WardLinkage
    extends Linkage
    Ward's linkage. Ward's linkage follows the analysis of variance approach The dissimilarity between two clusters is computed as the increase in the "error sum of squares" (ESS) after fusing two clusters into a single cluster. Ward's Method seeks to choose the successive clustering steps so as to minimize the increase in ESS at each step. Note that it is only valid for Euclidean distance based proximity matrix.
    Author:
    Haifeng Li
    • Constructor Summary

      Constructors 
      Constructor Description
      WardLinkage​(double[][] proximity)
      Constructor.
    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      void merge​(int i, int j)
      Merge two clusters into one and update the proximity matrix.
      java.lang.String toString()  
      • Methods inherited from class smile.clustering.linkage.Linkage

        d, size
      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
    • Constructor Detail

      • WardLinkage

        public WardLinkage​(double[][] proximity)
        Constructor.
        Parameters:
        proximity - the proximity matrix to store the distance measure of dissimilarity. To save space, we only need the lower half of matrix.
    • Method Detail

      • toString

        public java.lang.String toString()
        Overrides:
        toString in class java.lang.Object
      • merge

        public void merge​(int i,
                          int j)
        Description copied from class: Linkage
        Merge two clusters into one and update the proximity matrix.
        Specified by:
        merge in class Linkage
        Parameters:
        i - cluster id.
        j - cluster id.