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

Class LinearKernelFunction

java.lang.Object

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

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

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

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

All Implemented Interfaces:

DistanceFunction<NumberVector>, PrimitiveDistanceFunction<NumberVector>, PrimitiveSimilarityFunction<NumberVector>, SimilarityFunction<NumberVector>

public class LinearKernelFunction
extends PolynomialKernelFunction

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

Author:

Simon Paradies

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	distance(NumberVector fv1, NumberVector fv2) Computes the distance between two given DatabaseObjects according to this distance function.
double	similarity(NumberVector o1, NumberVector o2) Computes the similarity between two given DatabaseObjects according to this similarity function.

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

instantiate, isMetric

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

getInputTypeRestriction

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

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

similarity

public double similarity(NumberVector o1,
                NumberVector o2)

Description copied from interface: PrimitiveSimilarityFunction

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

Specified by:

similarity in interface PrimitiveSimilarityFunction<NumberVector>

Overrides:

similarity in class PolynomialKernelFunction

Parameters:

o1 - first DatabaseObject

o2 - second DatabaseObject

Returns:

the similarity between two given DatabaseObjects according to this similarity function

distance

public double distance(NumberVector fv1,
              NumberVector fv2)

Description copied from interface: PrimitiveDistanceFunction

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

Specified by:

distance in interface PrimitiveDistanceFunction<NumberVector>

Overrides:

distance in class PolynomialKernelFunction

Parameters:

fv1 - first DatabaseObject

fv2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function