Repository /Rseslib/rseslib-3.0.1.jar:rseslib.processing.classification.svm.SigmoidKernelFunction

/*
 * $RCSfile: Headerable.java,v $
 * $Revision: 1.10 $
 * $Date: 2006/07/29 12:39:52 $
 * $Author: wojna $
 * 
 * Copyright (C) 2002 - 2007 Logic Group, Institute of Mathematics, Warsaw University
 * 
 *  This file is part of Rseslib.
 *
 *  Rseslib 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 3 of the License, or
 *  (at your option) any later version.
 *
 *  Rseslib 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, see <http://www.gnu.org/licenses/>.
 */


package rseslib.processing.classification.svm;

import rseslib.structure.attribute.Header;
import rseslib.structure.data.DoubleData;
import rseslib.structure.table.DoubleDataTable;

/**
 * Class realizing sigmoid kernel function
 */
public class SigmoidKernelFunction implements KernelFunction {

    /** Information about attributes. */
    private Header m_Attributes;
    /**
     * kappa
     */
    private double kappa;
    /**
     * theta
     */
    private double theta;

    /**
     * Sigmoid function tanh(kappa*<x,y>+theta)
     * @param tab
     * @param k kappa
     * @param t theta
     */
    public SigmoidKernelFunction(DoubleDataTable tab, double k, double t) {
        m_Attributes = (Header)tab.attributes();
        kappa = k;
        theta = t;
    }

    /**
     * kernel function K
     * @param dObj1 data object 1
     * @param dObj2 data object 2
     * @return kernel function value for given parameters
     */
    public double K(DoubleData dObj1, DoubleData dObj2) {
        double result = 0;
        for (int att = 0; att < dObj1.attributes().noOfAttr(); att++)
            if (m_Attributes.isConditional(att))
                result+=dObj1.get(att)*dObj2.get(att);
        double x = result*kappa+theta;
        result = (Math.exp(x) - Math.exp(-x))/(Math.exp(x) + Math.exp(-x));
        return result;
    }

}