myklrmodel.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.operator.learner.kernel;

import edu.udo.cs.yale.example.Example;
import edu.udo.cs.yale.example.ExampleSet;
import edu.udo.cs.yale.example.Attribute;
import edu.udo.cs.yale.operator.OperatorException;
import edu.udo.cs.yale.tools.Ontology;

import edu.udo.cs.mySVM.SVM.*;
import edu.udo.cs.myKLR.*;
import edu.udo.cs.mySVM.Kernel.*;

import java.io.ObjectOutputStream;
import java.io.ObjectInputStream;

/** The model for the MyKLR learner by Stefan Rueping. 
 *
 *  @version $Id: MyKLRModel.java,v 1.3 2004/08/27 11:57:40 ingomierswa Exp $
 */
public class MyKLRModel extends AbstractMySVMModel {

    public MyKLRModel(Attribute labelAttribute) {
	super(labelAttribute);
    }

    public MyKLRModel(Attribute labelAttribute, 
		      edu.udo.cs.mySVM.Examples.ExampleSet model, 
		      Kernel kernel, 
		      int kernelType) {
	super(labelAttribute, model, kernel, kernelType);
    }

    public void apply(ExampleSet exampleSet) throws OperatorException {
	super.apply(exampleSet);
    }

    public SVMInterface createSVM() {
	return new KLR();
    }

    public void setPrediction(Example example, double prediction) {
	example.setPredictedLabel(prediction);
    }

    public Attribute createPredictedLabel(ExampleSet exampleSet, String name) {
	Attribute predictedLabel = super.createPredictedLabel(exampleSet, name);
	if (predictedLabel.isNominal())
	    predictedLabel.clearMaps();
	predictedLabel.setValueType(Ontology.REAL);
	return predictedLabel;
    }

}