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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) 2013
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.AbstractVectorDoubleDistanceFunction;
import de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractVectorDoubleSimilarityFunction;
import de.lmu.ifi.dbs.elki.utilities.Alias;
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;
/**
* Provides the Gaussian radial basis function kernel (RBF Kernel).
*
* @author Erich Schubert
*/
@Alias({ "rbf" })
public class RadialBasisFunctionKernelFunction extends AbstractVectorDoubleSimilarityFunction {
/**
* Scaling factor gamma. (= - 1/(2sigma^2))
*/
private final double gamma;
/**
* Constructor.
*
* @param sigma Scaling parameter sigma
*/
public RadialBasisFunctionKernelFunction(double sigma) {
super();
this.gamma = -.5 / (sigma * sigma);
}
@Override
public double doubleSimilarity(NumberVector<?> o1, NumberVector<?> o2) {
final int dim = AbstractVectorDoubleDistanceFunction.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 Math.exp(gamma * sim);
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public static class Parameterizer extends AbstractParameterizer {
/**
* Sigma parameter: standard deviation.
*/
public static final OptionID SIGMA_ID = new OptionID("kernel.rbf.sigma", "Standard deviation of the Gaussian RBF kernel.");
/**
* Sigma parameter
*/
protected double sigma = 1.;
@Override
protected void makeOptions(Parameterization config) {
super.makeOptions(config);
final DoubleParameter sigmaP = new DoubleParameter(SIGMA_ID, 1.);
sigmaP.addConstraint(CommonConstraints.GREATER_THAN_ZERO_DOUBLE);
if(config.grab(sigmaP)) {
sigma = sigmaP.doubleValue();
}
}
@Override
protected RadialBasisFunctionKernelFunction makeInstance() {
return new RadialBasisFunctionKernelFunction(sigma);
}
}
}
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