de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
Class FourC<O extends NumberVector<O,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<V,Clustering<Model>>
          de.lmu.ifi.dbs.elki.algorithm.clustering.ProjectedDBSCAN<O>
              de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC<O>

Type Parameters:

O - type of NumberVector handled by this Algorithm

All Implemented Interfaces:

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

@Title(value="4C: Computing Correlation Connected Clusters")
@Description(value="4C identifies local subgroups of data objects sharing a uniform correlation. The algorithm is based on a combination of PCA and density-based clustering (DBSCAN).")
@Reference(authors="C. B\u00f6hm, K. Kailing, P. Kr\u00f6ger, A. Zimek",
           title="Computing Clusters of Correlation Connected Objects",
           booktitle="Proc. ACM SIGMOD Int. Conf. on Management of Data, Paris, France, 2004, 455-466",
           url="http://dx.doi.org/10.1145/1007568.1007620")
public class FourC<O extends NumberVector<O,?>>
extends ProjectedDBSCAN<O>

4C identifies local subgroups of data objects sharing a uniform correlation. The algorithm is based on a combination of PCA and density-based clustering (DBSCAN).

Reference: Christian Böhm, Karin Kailing, Peer Kröger, Arthur Zimek: Computing Clusters of Correlation Connected Objects.
In Proc. ACM SIGMOD Int. Conf. on Management of Data, Paris, France, 2004.

Author:

Arthur Zimek

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

FourC(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

FourC

public FourC(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<O extends NumberVector<O,?>>

Returns:

the class actually used as VarianceAnalysisPreprocessor