de.lmu.ifi.dbs.elki.algorithm.clustering.subspace
Class PreDeCon<V extends NumberVector<V,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<R>
      de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedDBSCAN<Clustering<Model>,V>
          de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PreDeCon<V>

Type Parameters:

V - the type of NumberVector handled by this Algorithm

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<Model>>, InspectionUtilFrequentlyScanned, Parameterizable

@Title(value="PreDeCon: Subspace Preference weighted Density Connected Clustering")
@Description(value="PreDeCon computes clusters of subspace preference weighted connected points. The algorithm searches for local subgroups of a set of feature vectors having a low variance along one or more (but not all) attributes.")
@Reference(authors="C. B\u00f6hm, K. Kailing, H.-P. Kriegel, P. Kr\u00f6ger",
           title="Density Connected Clustering with Local Subspace Preferences",
           booktitle="Proc. 4th IEEE Int. Conf. on Data Mining (ICDM\'04), Brighton, UK, 2004",
           url="http://dx.doi.org/10.1109/ICDM.2004.10087")
public class PreDeCon<V extends NumberVector<V,?>>
extends AbstractProjectedDBSCAN<Clustering<Model>,V>

PreDeCon computes clusters of subspace preference weighted connected points. The algorithm searches for local subgroups of a set of feature vectors having a low variance along one or more (but not all) attributes.

Reference:
C. Böhm, K. Kailing, H.-P. Kriegel, P. Kröger: Density Connected Clustering with Local Subspace Preferences.
In Proc. 4th IEEE Int. Conf. on Data Mining (ICDM'04), Brighton, UK, 2004.

Nested Class Summary

static class

PreDeCon.Parameterizer<V extends NumberVector<V,?>> Parameterization class.

Field Summary

private static Logging

logger The logger for this class.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedDBSCAN

epsilon, EPSILON_ID, INNER_DISTANCE_FUNCTION_ID, LAMBDA_ID, minpts, MINPTS_ID, OUTER_DISTANCE_FUNCTION_ID

Constructor Summary

PreDeCon(DoubleDistance epsilon, int minpts, LocallyWeightedDistanceFunction<V> distanceFunction, int lambda)
Constructor.

Method Summary

protected Logging	getLogger() Get the (STATIC) logger for this class.
String	getLongResultName() Return the long result name.
String	getShortResultName() Return the short result name.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedDBSCAN

expandCluster, getInputTypeRestriction, run

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

makeParameterDistanceFunction, run

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.algorithm.clustering.ClusteringAlgorithm

run

Field Detail

logger

private static final Logging logger

The logger for this class.

Constructor Detail

PreDeCon

public PreDeCon(DoubleDistance epsilon,
                int minpts,
                LocallyWeightedDistanceFunction<V> distanceFunction,
                int lambda)

Constructor.

Parameters:

epsilon - Epsilon value

minpts - MinPts value

distanceFunction - outer distance function

lambda - Lambda value

Method Detail

getLongResultName

public String getLongResultName()

Description copied from class: AbstractProjectedDBSCAN

Return the long result name.

Specified by:

getLongResultName in class AbstractProjectedDBSCAN<Clustering<Model>,V extends NumberVector<V,?>>

Returns:

Long name for result

getShortResultName

public String getShortResultName()

Description copied from class: AbstractProjectedDBSCAN

Return the short result name.

Specified by:

getShortResultName in class AbstractProjectedDBSCAN<Clustering<Model>,V extends NumberVector<V,?>>

Returns:

Short name for result

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Specified by:

getLogger in class AbstractAlgorithm<Clustering<Model>>

Returns:

the static logger