package de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel; /* This file is part of ELKI: Environment for Developing KDD-Applications Supported by Index-Structures Copyright (C) 2015 Ludwig-Maximilians-Universität München Lehr- und Forschungseinheit für Datenbanksysteme ELKI Development Team 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 . */ import de.lmu.ifi.dbs.elki.data.NumberVector; import de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractNumberVectorDistanceFunction; import de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractVectorSimilarityFunction; import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer; import de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID; import de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.CommonConstraints; import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization; import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleParameter; /** * Rational quadratic kernel, a less computational approximation of the Gaussian * RBF kernel ({@link RadialBasisFunctionKernelFunction}). * * @author Erich Schubert */ public class RationalQuadraticKernelFunction extends AbstractVectorSimilarityFunction { /** * Constant term c. */ private final double c; /** * Constructor. * * @param c Constant term c. */ public RationalQuadraticKernelFunction(double c) { super(); this.c = c; } @Override public double similarity(NumberVector o1, NumberVector o2) { final int dim = AbstractNumberVectorDistanceFunction.dimensionality(o1, o2); double sim = 0.; for(int i = 0; i < dim; i++) { final double v = o1.doubleValue(i) - o2.doubleValue(i); sim += v * v; } return 1. - sim / (sim + c); } /** * Parameterization class. * * @author Erich Schubert * * @apiviz.exclude */ public static class Parameterizer extends AbstractParameterizer { /** * C parameter */ public static final OptionID C_ID = new OptionID("kernel.rationalquadratic.c", "Constant term in the rational quadratic kernel."); /** * C parameter */ protected double c = 1.; @Override protected void makeOptions(Parameterization config) { super.makeOptions(config); final DoubleParameter cP = new DoubleParameter(C_ID, 1.); cP.addConstraint(CommonConstraints.GREATER_THAN_ZERO_DOUBLE); if(config.grab(cP)) { c = cP.doubleValue(); } } @Override protected RationalQuadraticKernelFunction makeInstance() { return new RationalQuadraticKernelFunction(c); } } }