/* * RapidMiner * * Copyright (C) 2001-2008 by Rapid-I and the contributors * * Complete list of developers available at our web site: * * http://rapid-i.com * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU Affero General Public License as published by * the Free Software Foundation, either version 3 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 Affero General Public License for more details. * * You should have received a copy of the GNU Affero General Public License * along with this program. If not, see http://www.gnu.org/licenses/. */ package com.rapidminer.operator.learner.functions.kernel.rvm.kernel; /** * Returns the value of the Gaussian combination kernel of both examples. * * @author Ingo Mierswa * @version $Id: KernelGaussianCombination.java,v 1.3 2008/05/09 19:23:26 ingomierswa Exp $ */ public class KernelGaussianCombination extends Kernel { private static final long serialVersionUID = -8071778790596969872L; /** The parameter sigma1 of the Gaussian combination kernel. */ private double sigma1 = 1.0d; /** The parameter sigma2 of the Gaussian combination kernel. */ private double sigma2 = 0.0d; /** The parameter sigma3 of the Gaussian combination kernel. */ private double sigma3 = 2.0d; /** Constructor(s) */ public KernelGaussianCombination(double sigma1, double sigma2, double sigma3) { super(); this.sigma1 = sigma1; this.sigma2 = sigma2; this.sigma3 = sigma3; } public KernelGaussianCombination() { super(); } public double eval(double[] x, double[] y) { double norm2 = norm2(x, y); double exp1 = sigma1 == 0.0d ? 0.0d : Math.exp((-1) * norm2 / sigma1); double exp2 = sigma2 == 0.0d ? 0.0d : Math.exp((-1) * norm2 / sigma2); double exp3 = sigma3 == 0.0d ? 0.0d : Math.exp((-1) * norm2 / sigma3); return exp1 + exp2 - exp3; } public String toString() { return "gaussian combination kernel [sigma1 = " + sigma1 + ", sigma2 = " + sigma2 + ", sigma3 = " + sigma3 + "]"; } }