de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel

Class SigmoidKernelFunction

java.lang.Object

de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractPrimitiveSimilarityFunction<NumberVector<?>,DoubleDistance>

de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractVectorDoubleSimilarityFunction

de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.SigmoidKernelFunction

All Implemented Interfaces:

PrimitiveDoubleSimilarityFunction<NumberVector<?>>, PrimitiveSimilarityFunction<NumberVector<?>,DoubleDistance>, SimilarityFunction<NumberVector<?>,DoubleDistance>, Parameterizable

public class SigmoidKernelFunction
extends AbstractVectorDoubleSimilarityFunction

Sigmoid kernel function (aka: hyperbolic tangent kernel, multilayer perceptron MLP kernel).

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SigmoidKernelFunction.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private double	c Scaling factor c, bias theta
private double	theta Scaling factor c, bias theta

Constructor Summary

Constructors

Constructor and Description
SigmoidKernelFunction(double c, double theta) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
double	doubleSimilarity(NumberVector<?> o1, NumberVector<?> o2) Computes the similarity between two given Objects according to this similarity function.

Methods inherited from class de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractVectorDoubleSimilarityFunction

getDistanceFactory, getInputTypeRestriction, similarity

Methods inherited from class de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractPrimitiveSimilarityFunction

instantiate, isSymmetric

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface de.lmu.ifi.dbs.elki.distance.similarityfunction.SimilarityFunction

instantiate, isSymmetric

Field Detail

c

private final double c

Scaling factor c, bias theta

theta

private final double theta

Scaling factor c, bias theta

Constructor Detail

SigmoidKernelFunction

public SigmoidKernelFunction(double c,
                     double theta)

Constructor.

Parameters:

c - Scaling factor c.

theta - Bias parameter theta.

Method Detail

doubleSimilarity

public double doubleSimilarity(NumberVector<?> o1,
                      NumberVector<?> o2)

Description copied from interface: PrimitiveDoubleSimilarityFunction

Computes the similarity between two given Objects according to this similarity function.

Parameters:

o1 - first Object

o2 - second Object

Returns:

the similarity between two given Objects according to this similarity function