normalizationgenerator.java

一个很好的LIBSVM的JAVA源码。对于要研究和改进SVM算法的学者。可以参考。来自数据挖掘工具YALE工具包。

/*
 *  YALE - Yet Another Learning Environment
 *  Copyright (C) 2001-2004
 *      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.generator;

import edu.udo.cs.yale.tools.Ontology;
import edu.udo.cs.yale.tools.LogService;
import edu.udo.cs.yale.example.Attribute;
import edu.udo.cs.yale.example.ExampleTable;
import edu.udo.cs.yale.example.DataRow;
import edu.udo.cs.yale.example.ExampleSet;

/** Creates the normalized value of all input attributes, i.e. calculates <br>
 *  (value - min) / (max - min) for normalization between 0 and 1 and 
 *  (value - min) / (max - min) * (MAX - MIN) + MIN for
 *  normalization between MIN and MAX.
 *
 *  @version $Id: NormalizationGenerator.java,v 2.9 2004/08/27 11:57:33 ingomierswa Exp $
 */ 
public class NormalizationGenerator extends SingularNumericalGenerator {

    public static final String FUNCTION_NAME = "norm";

    private double min;
    private double max;

    /** Creates a new normalization generator. This generator normalizes the values between 0 and 1. */
    public NormalizationGenerator() {
	this(0.0d, 0.1d);
    }

    /** Creates a new normalization operator which normalizes the values between min and max. */
    public NormalizationGenerator(double min, double max) {
	this.min = min;
	this.max = max;
    }

    public FeatureGenerator newInstance() {
	return new NormalizationGenerator();
    }

    public double calculateValue(double value) {
	return Double.NaN;
    }

    public void generate(DataRow data) throws GenerationException {
	try {
	    Attribute a = getArgument(0);
	    double value = data.get(a);
	    double minA = a.getMinimum();
	    double maxA = a.getMaximum();
	    // if max = min or minA = maxA, all values are the same and are normalized to 0.0
	    double result = 0.0d;
	    if (((maxA - minA) != 0.0d) && ((max - min) != 0.0d)) {
		result = (value - minA) / (maxA - minA) * (max - min) + min; 
	    }
	    if (resultAttributes[0] != null)
		data.set(resultAttributes[0], result);
	} catch (ArrayIndexOutOfBoundsException ex) {
  	    throw new GenerationException("a1:" + getArgument(0));
  	}
    }

    public void setFunction(String name) {
	if (!FUNCTION_NAME.equals(name))
	    LogService.logMessage("Illegal function name '"+name+"' for "+getClass().getName()+".", 
				  LogService.ERROR);
    }

    public String getFunction() {
	return FUNCTION_NAME;
    }

}