de.lmu.ifi.dbs.elki.distance.distancefunction.correlation
Class AbstractCorrelationDistanceFunction<V extends FeatureVector<V,?>,P extends Preprocessor<V>,D extends CorrelationDistance<D>>

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,D>

Type Parameters:

V - the type of NumberVector used

P - the type of Preprocessor used

D - the type of CorrelationDistance used

All Implemented Interfaces:

DistanceFunction<V,D>, PreprocessorBasedDistanceFunction<V,P,D>, MeasurementFunction<V,D>, PreprocessorBasedMeasurementFunction<V,P,D>, PreprocessorClient<P,V>, Parameterizable

Direct Known Subclasses:

AbstractPreferenceVectorBasedCorrelationDistanceFunction, PCABasedCorrelationDistanceFunction

public abstract class AbstractCorrelationDistanceFunction<V extends FeatureVector<V,?>,P extends Preprocessor<V>,D extends CorrelationDistance<D>>
extends AbstractPreprocessorBasedDistanceFunction<V,P,D>

Abstract super class for correlation based distance functions. Provides the correlation distance for real valued vectors.

Author:

Elke Achtert

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

AbstractCorrelationDistanceFunction(Parameterization config, D distance)
Constructor, adhering to Parameterizable

Method Summary

protected abstract D	correlationDistance(V v1, V v2) Computes the correlation distance between the two specified vectors.
D	distance(V v1, V v2) Provides the Correlation distance between the given two vectors by calling correlationDistance(v1, v2).

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.preprocessing.PreprocessorClient

getAssociationID, getDefaultPreprocessorClass, getPreprocessorDescription, getPreprocessorSuperClass

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, undefinedDistance, valueOf

Constructor Detail

AbstractCorrelationDistanceFunction

public AbstractCorrelationDistanceFunction(Parameterization config,
                                           D distance)

Constructor, adhering to Parameterizable

Parameters:

config - Parameterization

distance - Distance Factory

Method Detail

distance

public final D distance(V v1,
                        V v2)

Provides the Correlation distance between the given two vectors by calling correlationDistance(v1, v2).

Parameters:

v1 - first DatabaseObject

v2 - second DatabaseObject

Returns:

the Correlation distance between the given two vectors as an instance of CorrelationDistance.

correlationDistance

protected abstract D correlationDistance(V v1,
                                         V v2)

Computes the correlation distance between the two specified vectors.

Parameters:

v1 - first vector

v2 - second vector

Returns:

the correlation distance between the two specified vectors