content: /*
   *    This program is free software; you can redistribute it and/or modify
   *    it under the terms of the GNU General Public License as published by
   *    the Free Software Foundation; either version 2 of the License, or
   *    (at your option) any later version.
   *
   *    This program is distributed in the hope that it will be useful,
   *    but WITHOUT ANY WARRANTY; without even the implied warranty of
   *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
   *    GNU General Public License for more details.
   *
   *    You should have received a copy of the GNU General Public License
   *    along with this program; if not, write to the Free Software
   *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
   */
  
  /*
   *    EntropySplitCrit.java
   *    Copyright (C) 1999 University of Waikato, Hamilton, New Zealand
   *
   */
  
  package weka.classifiers.trees.j48;
  
  import weka.core.RevisionUtils;
  import weka.core.Utils;
  
  /**
   * Class for computing the entropy for a given distribution.
   *
   * @author Eibe Frank (eibe@cs.waikato.ac.nz)
   * @version $Revision: 1.8 $
   */
  public final class EntropySplitCrit
    extends EntropyBasedSplitCrit {
  
    /** for serialization */
    private static final long serialVersionUID = 5986252682266803935L;
  
    /**
     * Computes entropy for given distribution.
     */
    public final double splitCritValue(Distribution bags) {
      
      return newEnt(bags);
    }
  
    /**
     * Computes entropy of test distribution with respect to training distribution.
     */
    public final double splitCritValue(Distribution train, Distribution test) {
  
      double result = 0;
      int numClasses = 0;
      int i, j;
      
      // Find out relevant number of classes
      for (j = 0; j < test.numClasses(); j++)
        if (Utils.gr(train.perClass(j), 0) || Utils.gr(test.perClass(j), 0))
  	numClasses++;
  
      // Compute entropy of test data with respect to training data
      for (i = 0; i < test.numBags(); i++)
        if (Utils.gr(test.perBag(i),0)) {
  	for (j = 0; j < test.numClasses(); j++)
  	  if (Utils.gr(test.perClassPerBag(i, j), 0))
  	    result -= test.perClassPerBag(i, j)*
  	      Math.log(train.perClassPerBag(i, j) + 1);
  	result += test.perBag(i) * Math.log(train.perBag(i) + numClasses);
        }
    
      return result / log2;
    }
    
    /**
     * Returns the revision string.
     * 
     * @return		the revision
     */
    public String getRevision() {
      return RevisionUtils.extract("$Revision: 1.8 $");
    }
  }
  