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

Class LinearKernelFunction

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.PolynomialKernelFunction

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

All Implemented Interfaces:

DistanceFunction<NumberVector<?>,DoubleDistance>, PrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>, PrimitiveDoubleDistanceFunction<NumberVector<?>>, PrimitiveDoubleSimilarityFunction<NumberVector<?>>, PrimitiveSimilarityFunction<NumberVector<?>,DoubleDistance>, SimilarityFunction<NumberVector<?>,DoubleDistance>, Parameterizable

public class LinearKernelFunction
extends PolynomialKernelFunction

Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 defined by V1^T*V2. Note: this is effectively equivalent to using EuclideanDistanceFunction

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
static LinearKernelFunction	STATIC Static instance.

Fields inherited from class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.PolynomialKernelFunction

DEFAULT_DEGREE

Constructor Summary

Constructors

Constructor and Description
LinearKernelFunction() Deprecated.

Method Summary

Methods

Modifier and Type	Method and Description
double	doubleDistance(NumberVector<?> fv1, NumberVector<?> fv2) Computes the distance between two given Objects according to this distance function.
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.kernel.PolynomialKernelFunction

distance, instantiate, isMetric

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

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.distancefunction.PrimitiveDistanceFunction

getInputTypeRestriction

Methods inherited from interface de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction

getDistanceFactory, isSymmetric

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

isSymmetric

Field Detail

STATIC

public static final LinearKernelFunction STATIC

Static instance.

Constructor Detail

LinearKernelFunction

@Deprecated
public LinearKernelFunction()

Deprecated.

Linear kernel. Use static instance STATIC!

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.

Specified by:

doubleSimilarity in interface PrimitiveDoubleSimilarityFunction<NumberVector<?>>

Overrides:

doubleSimilarity in class PolynomialKernelFunction

Parameters:

o1 - first Object

o2 - second Object

Returns:

the similarity between two given Objects according to this similarity function

doubleDistance

public double doubleDistance(NumberVector<?> fv1,
                    NumberVector<?> fv2)

Description copied from interface: PrimitiveDoubleDistanceFunction

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

Specified by:

doubleDistance in interface PrimitiveDoubleDistanceFunction<NumberVector<?>>

Overrides:

doubleDistance in class PolynomialKernelFunction

Parameters:

fv1 - first Object

fv2 - second Object

Returns:

the distance between two given Objects according to this distance function