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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 <http://www.gnu.org/licenses/>.
*/
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);
}
}
}
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