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

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.FooKernelFunction<O>

Type Parameters:

O - vector type

All Implemented Interfaces:

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

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

Provides an experimental KernelDistanceFunction for NumberVectors. Currently only supports 2D data and x1^2 ~ x2 correlations.

Author:

Simon Paradies

Field Summary

static int	DEFAULT_MAX_DEGREE The default max_degree.
private int	max_degree Degree of the polynomial kernel function
static OptionID	MAX_DEGREE_ID OptionID for MAX_DEGREE_PARAM
private IntParameter	MAX_DEGREE_PARAM Parameter for the maximum degree

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

FooKernelFunction(Parameterization config)
Constructor, adhering to Parameterizable

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 an experimental kernel similarity between the given two vectors.

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

Field Detail

DEFAULT_MAX_DEGREE

public static final int DEFAULT_MAX_DEGREE

The default max_degree.

See Also:

Constant Field Values

MAX_DEGREE_ID

public static final OptionID MAX_DEGREE_ID

OptionID for MAX_DEGREE_PARAM

MAX_DEGREE_PARAM

private final IntParameter MAX_DEGREE_PARAM

Parameter for the maximum degree

max_degree

private int max_degree

Degree of the polynomial kernel function

Constructor Detail

FooKernelFunction

public FooKernelFunction(Parameterization config)

Constructor, adhering to Parameterizable

Parameters:

config - Parameterization

Method Detail

similarity

public DoubleDistance similarity(O o1,
                                 O o2)

Provides an experimental kernel similarity between the given two vectors.

Parameters:

o1 - first vector

o2 - second vector

Returns:

the experimental 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