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

Class PolynomialKernelFunction

java.lang.Object

de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>

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

All Implemented Interfaces:

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

public class PolynomialKernelFunction
extends AbstractPrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>
implements PrimitiveSimilarityFunction<NumberVector<?>,DoubleDistance>

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

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_DEGREE The default degree.
private double	degree Degree of the polynomial kernel function.
static OptionID	DEGREE_ID Degree parameter.

Constructor Summary

Constructors

Constructor and Description
PolynomialKernelFunction(double degree) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
DoubleDistance	distance(NumberVector<?> fv1, NumberVector<?> fv2) Computes the distance between two given DatabaseObjects according to this distance function.
DoubleDistance	getDistanceFactory() Method to get the distance functions factory.
VectorFieldTypeInformation<? super NumberVector<?>>	getInputTypeRestriction() Get the input data type of the function.
<T extends NumberVector<?>> DistanceSimilarityQuery<T,DoubleDistance>	instantiate(Relation<T> database) Instantiate with a database to get the actual distance query.
DoubleDistance	similarity(NumberVector<?> o1, NumberVector<?> o2) Provides the linear kernel similarity between the given two vectors.

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

isMetric, 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

isSymmetric

Field Detail

DEFAULT_DEGREE

public static final double DEFAULT_DEGREE

The default degree.

See Also:

Constant Field Values

DEGREE_ID

public static final OptionID DEGREE_ID

Degree parameter.

degree

private double degree

Degree of the polynomial kernel function.

Constructor Detail

PolynomialKernelFunction

public PolynomialKernelFunction(double degree)

Constructor.

Parameters:

degree - Kernel degree

Method Detail

similarity

public DoubleDistance similarity(NumberVector<?> o1,
                        NumberVector<?> o2)

Provides the linear kernel similarity between the given two vectors.

Specified by:

similarity in interface PrimitiveSimilarityFunction<NumberVector<?>,DoubleDistance>

Parameters:

o1 - first vector

o2 - second vector

Returns:

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

distance

public DoubleDistance 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<?>,DoubleDistance>

Specified by:

distance in class AbstractPrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>

Parameters:

fv1 - first DatabaseObject

fv2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function

getInputTypeRestriction

public VectorFieldTypeInformation<? super NumberVector<?>> getInputTypeRestriction()

Description copied from interface: SimilarityFunction

Get the input data type of the function.

Specified by:

getInputTypeRestriction in interface DistanceFunction<NumberVector<?>,DoubleDistance>

Specified by:

getInputTypeRestriction in interface PrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>

Specified by:

getInputTypeRestriction in interface PrimitiveSimilarityFunction<NumberVector<?>,DoubleDistance>

Specified by:

getInputTypeRestriction in interface SimilarityFunction<NumberVector<?>,DoubleDistance>

Returns:

Type restriction

getDistanceFactory

public DoubleDistance getDistanceFactory()

Description copied from interface: DistanceFunction

Method to get the distance functions factory.

Specified by:

getDistanceFactory in interface DistanceFunction<NumberVector<?>,DoubleDistance>

Specified by:

getDistanceFactory in interface SimilarityFunction<NumberVector<?>,DoubleDistance>

Specified by:

getDistanceFactory in class AbstractPrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>

Returns:

Factory for distance objects

instantiate

public <T extends NumberVector<?>> DistanceSimilarityQuery<T,DoubleDistance> instantiate(Relation<T> database)

Description copied from class: AbstractPrimitiveDistanceFunction

Instantiate with a database to get the actual distance query.

Specified by:

instantiate in interface DistanceFunction<NumberVector<?>,DoubleDistance>

Specified by:

instantiate in interface SimilarityFunction<NumberVector<?>,DoubleDistance>

Overrides:

instantiate in class AbstractPrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>

Parameters:

database - Representation

Returns:

Actual distance query.