Package elki.evaluation.clustering.internal

Class VarianceRatioCriterion

  • All Implemented Interfaces:
    elki.evaluation.Evaluator, elki.result.ResultProcessor
    @Reference(authors="R. B. Calinski, J. Harabasz",
           title="A dendrite method for cluster analysis",
           booktitle="Communications in Statistics - Theory and Methods 3(1)",
           url="https://doi.org/10.1080/03610927408827101",
           bibkey="doi:10.1080/03610927408827101")
@Alias("calinski-harabasz")
public class VarianceRatioCriterion
extends java.lang.Object
implements elki.evaluation.Evaluator
    Compute the Variance Ratio Criterion of a data set, also known as Calinski-Harabasz index.

    Reference:

    R. B. Calinski, J. Harabasz
    A dendrite method for cluster analysis
    Communications in Statistics - Theory and Methods 3(1)

    Since:
    0.7.0
    Author:
    Stephan Baier, Erich Schubert

    • Nested Class Summary

      Nested Classes 
      Modifier and Type Class Description
      static class  VarianceRatioCriterion.Par
      Parameterization class.

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      double evaluateClustering​(elki.database.relation.Relation<? extends elki.data.NumberVector> rel, Clustering<?> c)
      Evaluate a single clustering.
      static int globalCentroid​(elki.math.linearalgebra.Centroid overallCentroid, elki.database.relation.Relation<? extends elki.data.NumberVector> rel, java.util.List<? extends Cluster<?>> clusters, elki.data.NumberVector[] centroids, NoiseHandling noiseOption)
      Update the global centroid.
      void processNewResult​(java.lang.Object result)  

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Field Detail

      • LOG

        private static final elki.logging.Logging LOG
        Logger for debug output.

      • noiseOption

        private NoiseHandling noiseOption
        Option for noise handling.

      • key

        private java.lang.String key
        Key for logging statistics.

    • Constructor Detail

      • VarianceRatioCriterion

        public VarianceRatioCriterion​(NoiseHandling noiseOption,
                              boolean penalize)
        Constructor.
        Parameters:
        noiseOption - Flag to control noise handling
        penalize - noise, if NoiseHandling.IGNORE_NOISE is set.

    • Method Detail

      • evaluateClustering

        public double evaluateClustering​(elki.database.relation.Relation<? extends elki.data.NumberVector> rel,
                                 Clustering<?> c)
        Evaluate a single clustering.
        Parameters:
        rel - Data relation
        c - Clustering
        Returns:
        Variance Ratio Criteria

      • globalCentroid

        public static int globalCentroid​(elki.math.linearalgebra.Centroid overallCentroid,
                                 elki.database.relation.Relation<? extends elki.data.NumberVector> rel,
                                 java.util.List<? extends Cluster<?>> clusters,
                                 elki.data.NumberVector[] centroids,
                                 NoiseHandling noiseOption)
        Update the global centroid.
        Parameters:
        overallCentroid - Centroid to udpate
        rel - Data relation
        clusters - Clusters
        centroids - Cluster centroids
        Returns:
        Number of clusters

      • processNewResult

        public void processNewResult​(java.lang.Object result)
        Specified by:
        processNewResult in interface elki.result.ResultProcessor