Environment for
DeveLoping
KDD-Applications
Supported by Index-Structures

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

java.lang.Object
  extended by de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      extended by de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<V,Clustering<Model>>
          extended by de.lmu.ifi.dbs.elki.algorithm.clustering.ProjectedDBSCAN<V>
              extended by 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<V,Clustering<Model>>, ClusteringAlgorithm<Clustering<Model>,V>, 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 ProjectedDBSCAN<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.

Author:
Peer Kröger

Field Summary
 
Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.ProjectedDBSCAN
epsilon, EPSILON_ID, INNER_DISTANCE_FUNCTION_ID, LAMBDA_ID, minpts, MINPTS_ID, OUTER_DISTANCE_FUNCTION_ID, OUTER_DISTANCE_FUNCTION_PARAM
 
Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable
debug, logger
 
Constructor Summary
PreDeCon(Parameterization config)
          Constructor, adhering to Parameterizable
 
Method Summary
 Class<?> preprocessorClass()
          Returns the class actually used as VarianceAnalysisPreprocessor.
 
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.ProjectedDBSCAN
expandCluster, runInTime
 
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm
isTime, isVerbose, run, setTime, setVerbose
 
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.algorithm.clustering.ClusteringAlgorithm
run
 
Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.Algorithm
setTime, setVerbose
 

Constructor Detail

PreDeCon

public PreDeCon(Parameterization config)
Constructor, adhering to Parameterizable

Parameters:
config - Parameterization
Method Detail

preprocessorClass

public Class<?> preprocessorClass()
Description copied from class: ProjectedDBSCAN
Returns the class actually used as VarianceAnalysisPreprocessor.

Specified by:
preprocessorClass in class ProjectedDBSCAN<V extends NumberVector<V,?>>
Returns:
the class actually used as VarianceAnalysisPreprocessor

Release 0.3 (2010-03-31_1612)