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.
   */
  
  /*
   *    SplitCriterion.java
   *    Copyright (C) 1999 University of Waikato, Hamilton, New Zealand
   *
   */
  
  package weka.classifiers.trees.j48;
  
  import weka.core.RevisionHandler;
  
  import java.io.Serializable;
  
  /**
   * Abstract class for computing splitting criteria
   * with respect to distributions of class values.
   *
   * @author Eibe Frank (eibe@cs.waikato.ac.nz)
   * @version $Revision: 1.8 $
   */
  public abstract class SplitCriterion
    implements Serializable, RevisionHandler {
  
    /** for serialization */
    private static final long serialVersionUID = 5490996638027101259L;
  
    /**
     * Computes result of splitting criterion for given distribution.
     *
     * @return value of splitting criterion. 0 by default
     */
    public double splitCritValue(Distribution bags){
  
      return 0;
    }
  
    /**
     * Computes result of splitting criterion for given training and
     * test distributions.
     *
     * @return value of splitting criterion. 0 by default
     */
    public double splitCritValue(Distribution train, Distribution test){
  
      return 0;
    }
  
    /**
     * Computes result of splitting criterion for given training and
     * test distributions and given number of classes.
     *
     * @return value of splitting criterion. 0 by default
     */
    public double splitCritValue(Distribution train, Distribution test,
  			       int noClassesDefault){
  
      return 0;
    }
  
    /**
     * Computes result of splitting criterion for given training and
     * test distributions and given default distribution.
     *
     * @return value of splitting criterion. 0 by default
     */
    public double splitCritValue(Distribution train, Distribution test,
  			       Distribution defC){
  
      return 0;
    }
  }
  
  
  