relativeerror.java

著名的开源仿真软件yale

/*
 *  YALE - Yet Another Learning Environment
 *  Copyright (C) 2002, 2003
 *      Simon Fischer, Ralf Klinkenberg, Ingo Mierswa, 
 *          Katharina Morik, Oliver Ritthoff
 *      Artificial Intelligence Unit
 *      Computer Science Department
 *      University of Dortmund
 *      44221 Dortmund,  Germany
 *  email: [e-mail]
 *  web:   http://yale.cs.uni-dortmund.de/
 *
 *  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., 59 Temple Place, Suite 330, Boston, MA 02111-1307
 *  USA.
 */
package edu.udo.cs.yale.operator.performance;

import edu.udo.cs.yale.example.Example;
import edu.udo.cs.yale.example.ExampleSet;
import edu.udo.cs.yale.tools.LogService;

/** A relative error. For each instance the error is calculated by
 *  dividing the difference of prediction and true label by the label. Hence,
 *  if the attribute set contains a single instance whose label is close to zero,
 *  the RelativeError is completely useless, since the relative error can easily be
 *  >> 1 for this example and this will greatly influence the average.
 *
 *  @author Oliver, Ingo, Simon
 *  @version $Id: RelativeError.java,v 2.3 2003/04/15 19:49:47 fischer Exp $
 */
public class RelativeError extends SimpleCriterion {

    public boolean formatPercent() { return true; }
    
    public String getName() {
	return "relative";
    }
    
    public double countExample(double label, double predictedLabel) {
      if (label == 0) { //rel. error undefined
        LogService.logMessage("Undefined relative error. Example skipped.", 
			      LogService.WARNING);
	return Double.NaN;
      } else { //rel. error defined
	  double absDifference = Math.abs(label-predictedLabel);
	  double rel = (absDifference)/label;
	  return rel;
      }
    }
}