kernelneural.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.mySVM.Kernel;
import edu.udo.cs.mySVM.Examples.*;
import java.io.*;

/**
 * Neural Kernel
 * @author Stefan R?ping, Ingo Mierswa (only Yale additions)
 * @version $Id: KernelNeural.java,v 1.3 2004/08/27 11:57:29 ingomierswa Exp $
 */
public class KernelNeural extends Kernel {
    double a = 1.0;
    double b = 0.0;

    /**
     * Class constructor
     */
    public KernelNeural(){};

    /**
     * Output as String
     */
    public String toString(){
	return("neural("+a+","+b+")");
    };
    
    public void setParameter(double a, double b) {
	this.a = a;
	this.b = b;
    }

    /**
     * Calculates kernel value of vectors x and y
     */
    public double calculate_K(int[] x_index,double[] x_att, int[] y_index, double[] y_att)
    {
	// K = tanh(a(x*y)+b)
	double prod = a*innerproduct(x_index,x_att,y_index,y_att)+b;
	double e1 = Math.exp(prod);
	double e2 = Math.exp(-prod);
	return ((e1-e2)/(e1+e2));
    };

    public void readKernelParameters(ObjectInputStream in) throws IOException {
	this.a = in.readDouble();
	this.b = in.readDouble();
    }

    public void writeKernelParameters(ObjectOutputStream out) throws IOException {
	out.writeDouble(this.a);
	out.writeDouble(this.b);
    }
};