Package weka.core

Class ContingencyTables

java.lang.Object
weka.core.ContingencyTables
All Implemented Interfaces:
RevisionHandler
public class ContingencyTables extends Object implements RevisionHandler
Class implementing some statistical routines for contingency tables.
Version:
$Revision: 10057 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)

  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    static final double
    log2
    The natural logarithm of 2

  • Constructor Summary

    Constructors
    Constructor
    Description
    ContingencyTables()
     

  • Method Summary

    Modifier and Type
    Method
    Description
    static double
    chiSquared(double[][] matrix, boolean yates)
    Returns chi-squared probability for a given matrix.
    static double
    chiVal(double[][] matrix, boolean useYates)
    Computes chi-squared statistic for a contingency table.
    static boolean
    cochransCriterion(double[][] matrix)
    Tests if Cochran's criterion is fullfilled for the given contingency table.
    static double
    CramersV(double[][] matrix)
    Computes Cramer's V for a contingency table.
    static double
    entropy(double[] array)
    Computes the entropy of the given array.
    static double
    entropyConditionedOnColumns(double[][] matrix)
    Computes conditional entropy of the rows given the columns.
    static double
    entropyConditionedOnRows(double[][] matrix)
    Computes conditional entropy of the columns given the rows.
    static double
    entropyConditionedOnRows(double[][] train, double[][] test, double numClasses)
    Computes conditional entropy of the columns given the rows of the test matrix with respect to the train matrix.
    static double
    entropyOverColumns(double[][] matrix)
    Computes the columns' entropy for the given contingency table.
    static double
    entropyOverRows(double[][] matrix)
    Computes the rows' entropy for the given contingency table.
    static double
    gainRatio(double[][] matrix)
    Computes gain ratio for contingency table (split on rows).
    String
    getRevision()
    Returns the revision string.
    static double
    lnFunc(double num)
    Help method for computing entropy.
    static double
    log2MultipleHypergeometric(double[][] matrix)
    Returns negative base 2 logarithm of multiple hypergeometric probability for a contingency table.
    static void
    main(String[] ops)
    Main method for testing this class.
    static double[][]
    reduceMatrix(double[][] matrix)
    Reduces a matrix by deleting all zero rows and columns.
    static double
    symmetricalUncertainty(double[][] matrix)
    Calculates the symmetrical uncertainty for base 2.
    static double
    tauVal(double[][] matrix)
    Computes Goodman and Kruskal's tau-value for a contingency table.

    Methods inherited from class java.lang.Object

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

  • Field Details

    • log2

      public static final double log2
      The natural logarithm of 2

  • Constructor Details

    • ContingencyTables

      public ContingencyTables()

  • Method Details

    • chiSquared

      public static double chiSquared(double[][] matrix, boolean yates)
      Returns chi-squared probability for a given matrix.
      Parameters:
      matrix - the contigency table
      yates - is Yates' correction to be used?
      Returns:
      the chi-squared probability

    • chiVal

      public static double chiVal(double[][] matrix, boolean useYates)
      Computes chi-squared statistic for a contingency table.
      Parameters:
      matrix - the contigency table
      useYates - is Yates' correction to be used?
      Returns:
      the value of the chi-squared statistic

    • cochransCriterion

      public static boolean cochransCriterion(double[][] matrix)
      Tests if Cochran's criterion is fullfilled for the given contingency table. Rows and columns with all zeros are not considered relevant.
      Parameters:
      matrix - the contigency table to be tested
      Returns:
      true if contingency table is ok, false if not

    • CramersV

      public static double CramersV(double[][] matrix)
      Computes Cramer's V for a contingency table.
      Parameters:
      matrix - the contingency table
      Returns:
      Cramer's V

    • entropy

      public static double entropy(double[] array)
      Computes the entropy of the given array.
      Parameters:
      array - the array
      Returns:
      the entropy

    • entropyConditionedOnColumns

      public static double entropyConditionedOnColumns(double[][] matrix)
      Computes conditional entropy of the rows given the columns.
      Parameters:
      matrix - the contingency table
      Returns:
      the conditional entropy of the rows given the columns

    • entropyConditionedOnRows

      public static double entropyConditionedOnRows(double[][] matrix)
      Computes conditional entropy of the columns given the rows.
      Parameters:
      matrix - the contingency table
      Returns:
      the conditional entropy of the columns given the rows

    • entropyConditionedOnRows

      public static double entropyConditionedOnRows(double[][] train, double[][] test, double numClasses)
      Computes conditional entropy of the columns given the rows of the test matrix with respect to the train matrix. Uses a Laplace prior. Does NOT normalize the entropy.
      Parameters:
      train - the train matrix
      test - the test matrix
      numClasses - the number of symbols for Laplace
      Returns:
      the entropy

    • entropyOverRows

      public static double entropyOverRows(double[][] matrix)
      Computes the rows' entropy for the given contingency table.
      Parameters:
      matrix - the contingency table
      Returns:
      the rows' entropy

    • entropyOverColumns

      public static double entropyOverColumns(double[][] matrix)
      Computes the columns' entropy for the given contingency table.
      Parameters:
      matrix - the contingency table
      Returns:
      the columns' entropy

    • gainRatio

      public static double gainRatio(double[][] matrix)
      Computes gain ratio for contingency table (split on rows). Returns Double.MAX_VALUE if the split entropy is 0.
      Parameters:
      matrix - the contingency table
      Returns:
      the gain ratio

    • log2MultipleHypergeometric

      public static double log2MultipleHypergeometric(double[][] matrix)
      Returns negative base 2 logarithm of multiple hypergeometric probability for a contingency table.
      Parameters:
      matrix - the contingency table
      Returns:
      the log of the hypergeometric probability of the contingency table

    • reduceMatrix

      public static double[][] reduceMatrix(double[][] matrix)
      Reduces a matrix by deleting all zero rows and columns.
      Parameters:
      matrix - the matrix to be reduced
      Returns:
      the matrix with all zero rows and columns deleted

    • symmetricalUncertainty

      public static double symmetricalUncertainty(double[][] matrix)
      Calculates the symmetrical uncertainty for base 2.
      Parameters:
      matrix - the contingency table
      Returns:
      the calculated symmetrical uncertainty

    • tauVal

      public static double tauVal(double[][] matrix)
      Computes Goodman and Kruskal's tau-value for a contingency table.
      Parameters:
      matrix - the contingency table
      Returns:
      Goodman and Kruskal's tau-value

    • lnFunc

      public static double lnFunc(double num)
      Help method for computing entropy.

    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      Returns:
      the revision

    • main

      public static void main(String[] ops)
      Main method for testing this class.