de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel
Class LinearKernelFunction<O extends NumberVector<O,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.distance.AbstractMeasurementFunction<O,D>
          de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDistanceFunction<O,D>
              de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.AbstractKernelFunction<O,DoubleDistance>
                  de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.LinearKernelFunction<O>

Type Parameters:

O - vector type

All Implemented Interfaces:

DistanceFunction<O,DoubleDistance>, MeasurementFunction<O,DoubleDistance>, KernelFunction<O,DoubleDistance>, SimilarityFunction<O,DoubleDistance>, Parameterizable

public class LinearKernelFunction<O extends NumberVector<O,?>>
extends AbstractKernelFunction<O,DoubleDistance>

Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 defined by V1^T*V2.

Author:

Simon Paradies

Field Summary

Fields inherited from class de.lmu.ifi.dbs.elki.distance.AbstractMeasurementFunction

distanceFactory

Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debug, logger

Constructor Summary

LinearKernelFunction()
Provides a linear Kernel function that computes a similarity between the two vectors V1 and V2 defined by V1^T*V2.

Method Summary

DoubleDistance	distance(O fv1, O fv2) Computes the distance between two given DatabaseObjects according to this distance function.
DoubleDistance	similarity(O o1, O o2) Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 definded by V1^T*V2

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

similarity, similarity

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDistanceFunction

distance, distance

Methods inherited from class de.lmu.ifi.dbs.elki.distance.AbstractMeasurementFunction

getDatabase, getDistanceFactory, infiniteDistance, nullDistance, setDatabase, undefinedDistance, valueOf

Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debugFine, debugFiner, debugFinest, exception, progress, verbose, warning

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.DistanceFunction

distance, distance

Methods inherited from interface de.lmu.ifi.dbs.elki.distance.MeasurementFunction

getDistanceFactory, infiniteDistance, nullDistance, setDatabase, undefinedDistance, valueOf

Constructor Detail

LinearKernelFunction

public LinearKernelFunction()

Provides a linear Kernel function that computes a similarity between the two vectors V1 and V2 defined by V1^T*V2.

Method Detail

similarity

public DoubleDistance similarity(O o1,
                                 O o2)

Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 definded by V1^T*V2

Parameters:

o1 - first feature vector

o2 - second feature vector

Returns:

the linear kernel similarity between the given two vectors as an instance of DoubleDistance.

distance

public DoubleDistance distance(O fv1,
                               O fv2)

Description copied from interface: DistanceFunction

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

Parameters:

fv1 - first DatabaseObject

fv2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function