Package elki.itemsetmining.associationrules.interest

Class CertaintyFactor

  • All Implemented Interfaces:
    InterestingnessMeasure
    @Reference(authors="F. Berzal, I. Blanco, D. S\u00e1nchez, M. Vila",
           title="Measuring the accuracy and interest of association rules: A new framework",
           booktitle="Intelligent Data Analysis, 6(3), 2002",
           url="http://content.iospress.com/articles/intelligent-data-analysis/ida00089",
           bibkey="DBLP:journals/ida/GalianoBSM02")
@Alias("Loevinger")
public class CertaintyFactor
extends java.lang.Object
implements InterestingnessMeasure
    Certainty factor (CF; Loevinger) interestingness measure. \( \tfrac{\text{confidence}(X \rightarrow Y) - \text{support}(Y)}{\text{support}(\neg Y)} \).

    Reference:

    F. Berzal, I. Blanco, D. Sánchez, M. Vila
    Measuring the accuracy and interest of association rules: A new framework
    Intelligent Data Analysis, 6(3), 2002

    Since:
    0.7.5
    Author:
    Frederic Sautter

    • Constructor Summary

      Constructors 
      Constructor Description
      CertaintyFactor()
      Constructor.

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      double measure​(int t, int sX, int sY, int sXY)
      Computes the value of the measure for a given support values

      • Methods inherited from class java.lang.Object

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

    • Constructor Detail

      • CertaintyFactor

        public CertaintyFactor()
        Constructor.

    • Method Detail

      • measure

        public double measure​(int t,
                      int sX,
                      int sY,
                      int sXY)
        Description copied from interface: InterestingnessMeasure
        Computes the value of the measure for a given support values
        Specified by:
        measure in interface InterestingnessMeasure
        Parameters:
        t - Total number of transaction
        sX - Support of the antecedent
        sY - Support of the consequent
        sXY - Support of the union of antecedent and consequent
        Returns:
        value of the measure