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.
   */
  
  /*
   *    HoldOutSubsetEvaluator.java
   *    Copyright (C) 2000 University of Waikato, Hamilton, New Zealand
   *
   */
  
  package weka.attributeSelection;
  
  import weka.core.Instance;
  import weka.core.Instances;
  
  import java.util.BitSet;
  
  /** 
   * Abstract attribute subset evaluator capable of evaluating subsets with
   * respect to a data set that is distinct from that used to initialize/
   * train the subset evaluator.
   *
   * @author Mark Hall (mhall@cs.waikato.ac.nz)
   * @version $Revision: 1.7 $
   */
  public abstract class HoldOutSubsetEvaluator 
    extends ASEvaluation
    implements SubsetEvaluator {
  
    /** for serialization */
    private static final long serialVersionUID = 8280529785412054174L;
    
    /**
     * Evaluates a subset of attributes with respect to a set of instances.
     * @param subset a bitset representing the attribute subset to be
     * evaluated
     * @param holdOut a set of instances (possibly seperate and distinct
     * from those use to build/train the evaluator) with which to
     * evaluate the merit of the subset
     * @return the "merit" of the subset on the holdOut data
     * @exception Exception if the subset cannot be evaluated
     */
    public abstract double evaluateSubset(BitSet subset, Instances holdOut)
      throws Exception;
  
    /**
     * Evaluates a subset of attributes with respect to a single instance.
     * @param subset a bitset representing the attribute subset to be
     * evaluated
     * @param holdOut a single instance (possibly not one of those used to
     * build/train the evaluator) with which to evaluate the merit of the subset
     * @param retrain true if the classifier should be retrained with respect
     * to the new subset before testing on the holdOut instance.
     * @return the "merit" of the subset on the holdOut instance
     * @exception Exception if the subset cannot be evaluated
     */
    public abstract double evaluateSubset(BitSet subset, 
  					Instance holdOut,
  					boolean retrain)
      throws Exception;
  }
  