Overview | Package | Class | Tree | Deprecated | Index | Help | Weka's home
PREV CLASS NEXT CLASS | FRAMES NO FRAMES
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD

## weka.core
Class ContingencyTables

    java.lang.Object
      weka.core.ContingencyTables

    public class ContingencyTables

extends java.lang.Object

Class implementing some statistical routines for contingency tables.

Version:
  $Revision: 1.5 $
Author:
  Eibe Frank (eibe@cs.waikato.ac.nz)

Constructor Summary
`ContingencyTables()`

Method Summary
`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).
`static double` | `log2MultipleHypergeometric(double[][] matrix)` Returns negative base 2 logarithm of multiple hypergeometric probability for a contingency table.
`static void` | `main(java.lang.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`

Constructor Detail

### ContingencyTables

    public ContingencyTables()

Method Detail

### 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
    `yates` - 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
    `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
    `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
    `Goodman` - and Kruskal's tau-value

### main

    public static void main(java.lang.String[] ops)

  Main method for testing this class.

Overview | Package | Class | Tree | Deprecated | Index | Help | Weka's home
PREV CLASS NEXT CLASS | FRAMES NO FRAMES
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD