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Class weka.core.ContingencyTables

java.lang.Object
   |
   +----weka.core.ContingencyTables

public class ContingencyTables

extends Object

Version:

$Revision: 1.2 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

ContingencyTables()

chiSquared(double[][], boolean)

Returns chi-squared probability for a given matrix.

chiVal(double[][], boolean)

Computes chi-squared statistic for a contingency table.

cochransCriterion(double[][])

Tests if Cochran's criterion is fullfilled for the given contingency table.

CramersV(double[][])

Computes Cramer's V for a contingency table.

entropy(double[])

Computes the entropy of the given array.

entropyConditionedOnColumns(double[][])

Computes conditional entropy of the rows given the columns.

entropyConditionedOnRows(double[][])

Computes conditional entropy of the columns given the rows.

entropyConditionedOnRows(double[][], double[][], double)

Computes conditional entropy of the columns given the rows of the test matrix with respect to the train matrix.

entropyOverColumns(double[][])

Computes the columns' entropy for the given contingency table.

entropyOverRows(double[][])

Computes the rows' entropy for the given contingency table.

gainRatio(double[][])

Computes gain ratio for contingency table (split on rows).

log2MultipleHypergeometric(double[][])

Returns negative base 2 logarithm of multiple hypergeometric probability for a contingency table.

main(String[])

Main method for testing this class.

reduceMatrix(double[][])

Reduces a matrix by deleting all zero rows and columns.

symmetricalUncertainty(double[][])

Calculates the symmetrical uncertainty for base 2.

tauVal(double[][])

Computes Goodman and Kruskal's tau-value for a contingency table.

 public ContingencyTables()

 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

 public static double chiVal(double matrix[][],
                             boolean useYates)

Computes chi-squared statistic for a contingency table.

Parameters:

matrix - the contigency table

yates - is Yates' correction to be used?

Returns:

the value of the chi-squared statistic

 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

 public static double CramersV(double matrix[][])

Computes Cramer's V for a contingency table.

Parameters:

matrix - the contingency table

Returns:

Cramer's V

 public static double entropy(double array[])

Computes the entropy of the given array.

Parameters:

array - the array

Returns:

the entropy

 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

 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

 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

the - number of symbols for Laplace

Returns:

the entropy

 public static double entropyOverRows(double matrix[][])

Computes the rows' entropy for the given contingency table.

Parameters:

matrix - the contingency table

Returns:

the rows' entropy

 public static double entropyOverColumns(double matrix[][])

Computes the columns' entropy for the given contingency table.

Parameters:

matrix - the contingency table

Returns:

the columns' entropy

 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

 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

 public static double[][] reduceMatrix(double matrix[][])

Reduces a matrix by deleting all zero rows and columns.

Parameters:

matrix - the matrix to be reduced

the - matrix with all zero rows and columns deleted

 public static double symmetricalUncertainty(double matrix[][])

Calculates the symmetrical uncertainty for base 2.

Parameters:

matrix - the contingency table

Returns:

the calculated symmetrical uncertainty

 public static double tauVal(double matrix[][])

Computes Goodman and Kruskal's tau-value for a contingency table.

Parameters:

matrix - the contingency table

Goodman - and Kruskal's tau-value

 public static void main(String ops[])

Main method for testing this class.

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