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

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable
          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.AbstractDoubleKernelFunction<O>
                          de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.PolynomialKernelFunction<O>

All Implemented Interfaces:

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

public class PolynomialKernelFunction<O extends FeatureVector<O,?>>
extends AbstractDoubleKernelFunction<O>

Provides a polynomial Kernel function that computes a similarity between the two feature vectors V1 and V2 definded by (V1^T*V2)^degree.

Author:

Simon Paradies

Field Summary

static double	DEFAULT_DEGREE The default degree.
private double	degree Degree of the polynomial kernel function
static String	DEGREE_D Description for parameter degree.
static String	DEGREE_P Parameter for degree.

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

INFINITY_PATTERN

Fields inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable

optionHandler

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

debug

Constructor Summary

PolynomialKernelFunction()
Provides a polynomial Kernel function that computes a similarity between the two feature vectors V1 and V2 definded by (V1^T*V2)^degree.

Method Summary

String	description() Returns a description of the class and the required parameters.
String[]	setParameters(String[] args) Sets the attributes of the class accordingly to the given parameters.
DoubleDistance	similarity(O o1, O o2) Provides the linear kernel similarity between the given two vectors.

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

distance, infiniteDistance, nullDistance, undefinedDistance, valueOf

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, isInfiniteDistance, isNullDistance, isUndefinedDistance

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

getDatabase, matches, requiredInputPattern, setDatabase, setRequiredInputPattern

Methods inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable

addOption, checkGlobalParameterConstraints, deleteOption, description, description, getAttributeSettings, getParameters, getParameterValue, getPossibleOptions, inlineDescription, isSet, setParameters

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

debugFine, debugFiner, debugFinest, exception, message, progress, progress, progress, verbose, 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

isInfiniteDistance, isNullDistance, isUndefinedDistance, requiredInputPattern, setDatabase

Methods inherited from interface de.lmu.ifi.dbs.elki.utilities.optionhandling.Parameterizable

checkGlobalParameterConstraints, getAttributeSettings, getParameters, getPossibleOptions, inlineDescription

Field Detail

DEFAULT_DEGREE

public static final double DEFAULT_DEGREE

The default degree.

See Also:

Constant Field Values

DEGREE_D

public static final String DEGREE_D

Description for parameter degree.

See Also:

Constant Field Values

DEGREE_P

public static final String DEGREE_P

Parameter for degree.

See Also:

Constant Field Values

degree

private double degree

Degree of the polynomial kernel function

Constructor Detail

PolynomialKernelFunction

public PolynomialKernelFunction()

Provides a polynomial Kernel function that computes a similarity between the two feature vectors V1 and V2 definded by (V1^T*V2)^degree.

Method Detail

description

public String description()

Description copied from interface: Parameterizable

Returns a description of the class and the required parameters.

This description should be suitable for a usage description as for a standalone application.

Specified by:

description in interface Parameterizable

Overrides:

description in class AbstractParameterizable

Returns:

String a description of the class and the required parameters

See Also:

Parameterizable.description()

setParameters

public String[] setParameters(String[] args)
                       throws ParameterException

Description copied from interface: Parameterizable

Sets the attributes of the class accordingly to the given parameters. Returns a new String array containing those entries of the given array that are neither expected nor used by this Parameterizable.

Specified by:

setParameters in interface Parameterizable

Overrides:

setParameters in class AbstractParameterizable

Parameters:

args - parameters to set the attributes accordingly to

Returns:

String[] an array containing the unused parameters

Throws:

ParameterException

See Also:

Parameterizable.setParameters(String[])

similarity

public DoubleDistance similarity(O o1,
                                 O o2)

Provides the linear kernel similarity between the given two vectors.

Parameters:

o1 - first vector

o2 - second vector

Returns:

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

See Also:

DistanceFunction.distance(de.lmu.ifi.dbs.elki.data.DatabaseObject, de.lmu.ifi.dbs.elki.data.DatabaseObject)