de.lmu.ifi.dbs.elki.distance.distancefunction.correlation
Class PCABasedCorrelationDistanceFunction<V extends NumberVector<V,?>,P extends LocalPCAPreprocessor<V>>

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.distancefunction.AbstractPreprocessorBasedDistanceFunction<V,P,D>
                  de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbstractCorrelationDistanceFunction<V,P,PCACorrelationDistance>
                      de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.PCABasedCorrelationDistanceFunction<V,P>

Type Parameters:

V - the type of NumberVector to compute the distances in between

P - the type of Preprocessor used

All Implemented Interfaces:

DistanceFunction<V,PCACorrelationDistance>, LocalPCAPreprocessorBasedDistanceFunction<V,P,PCACorrelationDistance>, PreprocessorBasedDistanceFunction<V,P,PCACorrelationDistance>, MeasurementFunction<V,PCACorrelationDistance>, PreprocessorBasedMeasurementFunction<V,P,PCACorrelationDistance>, PreprocessorClient<P,V>, Parameterizable

public class PCABasedCorrelationDistanceFunction<V extends NumberVector<V,?>,P extends LocalPCAPreprocessor<V>>
extends AbstractCorrelationDistanceFunction<V,P,PCACorrelationDistance>
implements LocalPCAPreprocessorBasedDistanceFunction<V,P,PCACorrelationDistance>

Provides the correlation distance for real valued vectors.

Author:

Elke Achtert

Field Summary

private double	delta Holds the value of DELTA_PARAM.
static OptionID	DELTA_ID OptionID for DELTA_PARAM
private DoubleParameter	DELTA_PARAM Parameter to specify the threshold of a distance between a vector q and a given space that indicates that q adds a new dimension to the space, must be a double equal to or greater than 0.

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

PCABasedCorrelationDistanceFunction(Parameterization config)
Constructor, adhering to Parameterizable

Method Summary

private void	adjust(Matrix v, Matrix e_czech, Matrix vector, int corrDim) Inserts the specified vector into the given orthonormal matrix v at column corrDim.
int	correlationDistance(PCAFilteredResult pca1, PCAFilteredResult pca2, int dimensionality) Computes the correlation distance between the two subspaces defined by the specified PCAs.
protected PCACorrelationDistance	correlationDistance(V dv1, V dv2) Computes the correlation distance between the two specified vectors.
private double	euclideanDistance(V dv1, V dv2) Computes the Euclidean distance between the given two vectors.
AssociationID<?>	getAssociationID() Returns the association ID for the association to be set by the preprocessor.
Class<?>	getDefaultPreprocessorClass() Returns the name of the default preprocessor.
String	getPreprocessorDescription() Returns the description for the preprocessor parameter.
Class<P>	getPreprocessorSuperClass() Returns the super class for the preprocessor parameter.

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

distance

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

getPreprocessor, setDatabase

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, 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, distance

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

getDistanceFactory, infiniteDistance, nullDistance, setDatabase, undefinedDistance, valueOf

Field Detail

DELTA_ID

public static final OptionID DELTA_ID

OptionID for DELTA_PARAM

DELTA_PARAM

private final DoubleParameter DELTA_PARAM

Parameter to specify the threshold of a distance between a vector q and a given space that indicates that q adds a new dimension to the space, must be a double equal to or greater than 0.

Default value: 0.25

Key: -pcabasedcorrelationdf.delta

delta

private double delta

Holds the value of DELTA_PARAM.

Constructor Detail

PCABasedCorrelationDistanceFunction

public PCABasedCorrelationDistanceFunction(Parameterization config)

Constructor, adhering to Parameterizable

Parameters:

config - Parameterization

Method Detail

correlationDistance

protected PCACorrelationDistance correlationDistance(V dv1,
                                                     V dv2)

Description copied from class: AbstractCorrelationDistanceFunction

Computes the correlation distance between the two specified vectors.

Specified by:

correlationDistance in class AbstractCorrelationDistanceFunction<V extends NumberVector<V,?>,P extends LocalPCAPreprocessor<V>,PCACorrelationDistance>

Parameters:

dv1 - first vector

dv2 - second vector

Returns:

the correlation distance between the two specified vectors

correlationDistance

public int correlationDistance(PCAFilteredResult pca1,
                               PCAFilteredResult pca2,
                               int dimensionality)

Computes the correlation distance between the two subspaces defined by the specified PCAs.

Parameters:

pca1 - first PCA

pca2 - second PCA

dimensionality - the dimensionality of the data space

Returns:

the correlation distance between the two subspaces defined by the specified PCAs

adjust

private void adjust(Matrix v,
                    Matrix e_czech,
                    Matrix vector,
                    int corrDim)

Inserts the specified vector into the given orthonormal matrix v at column corrDim. After insertion the matrix v is orthonormalized and column corrDim of matrix e_czech is set to the corrDim-th unit vector..

Parameters:

v - the orthonormal matrix of the eigenvectors

e_czech - the selection matrix of the strong eigenvectors

vector - the vector to be inserted

corrDim - the column at which the vector should be inserted

euclideanDistance

private double euclideanDistance(V dv1,
                                 V dv2)

Computes the Euclidean distance between the given two vectors.

Parameters:

dv1 - first FeatureVector

dv2 - second FeatureVector

Returns:

the Euclidean distance between the given two vectors

getDefaultPreprocessorClass

public Class<?> getDefaultPreprocessorClass()

Description copied from interface: PreprocessorClient

Returns the name of the default preprocessor.

Specified by:

getDefaultPreprocessorClass in interface PreprocessorClient<P extends LocalPCAPreprocessor<V>,V extends NumberVector<V,?>>

Returns:

the name of the default preprocessor, which is KnnQueryBasedLocalPCAPreprocessor

getPreprocessorDescription

public String getPreprocessorDescription()

Description copied from interface: PreprocessorClient

Returns the description for the preprocessor parameter.

Specified by:

getPreprocessorDescription in interface PreprocessorClient<P extends LocalPCAPreprocessor<V>,V extends NumberVector<V,?>>

Returns:

the description for the preprocessor parameter

getPreprocessorSuperClass

public Class<P> getPreprocessorSuperClass()

Description copied from interface: PreprocessorClient

Returns the super class for the preprocessor parameter.

Specified by:

getPreprocessorSuperClass in interface PreprocessorClient<P extends LocalPCAPreprocessor<V>,V extends NumberVector<V,?>>

Returns:

the super class for the preprocessor parameter, which is LocalPCAPreprocessor

getAssociationID

public AssociationID<?> getAssociationID()

Description copied from interface: PreprocessorClient

Returns the association ID for the association to be set by the preprocessor.

Specified by:

getAssociationID in interface PreprocessorClient<P extends LocalPCAPreprocessor<V>,V extends NumberVector<V,?>>

Returns:

the association ID for the association to be set by the preprocessor, which is AssociationID.LOCAL_PCA