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

java.lang.Object
  extended by de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<R>
      extended by de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<O,D,ClusterOrderResult<D>>
          extended by de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS<V,PCACorrelationDistance>
              extended by de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO<V>
Type Parameters:
V - the type of NumberVector handled by the algorithm
All Implemented Interfaces:
Algorithm, OPTICSTypeAlgorithm<PCACorrelationDistance>, InspectionUtilFrequentlyScanned, Parameterizable

@Title(value="Mining Hierarchies of Correlation Clusters")
@Description(value="Algorithm for detecting hierarchies of correlation clusters.")
@Reference(authors="E. Achtert, C. B\u00f6hm, P. Kr\u00f6ger, A. Zimek",
           title="Mining Hierarchies of Correlation Clusterse",
           booktitle="Proc. Int. Conf. on Scientific and Statistical Database Management (SSDBM\'06), Vienna, Austria, 2006",
           url="http://dx.doi.org/10.1109/SSDBM.2006.35")
public class HiCO<V extends NumberVector<V,?>>
extends OPTICS<V,PCACorrelationDistance>

Implementation of the HiCO algorithm, an algorithm for detecting hierarchies of correlation clusters.

Reference: E. Achtert, C. Böhm, P. Kröger, A. Zimek: Mining Hierarchies of Correlation Clusters.
In: Proc. Int. Conf. on Scientific and Statistical Database Management (SSDBM'06), Vienna, Austria, 2006.


Nested Class Summary
static class HiCO.Parameterizer<V extends NumberVector<V,?>>
          Parameterization class.
 
Field Summary
static OptionID ALPHA_ID
          The threshold for 'strong' eigenvectors: the 'strong' eigenvectors explain a portion of at least alpha of the total variance.
static double DEFAULT_ALPHA
          The default value for ALPHA_ID.
static double DEFAULT_DELTA
          The default value for DELTA_ID.
static OptionID DELTA_ID
          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.
static OptionID K_ID
          Optional parameter to specify the number of nearest neighbors considered in the PCA, must be an integer greater than 0.
private static Logging logger
          The logger for this class.
static OptionID MU_ID
          Parameter to specify the smoothing factor, must be an integer greater than 0.
 
Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS
EPSILON_ID, MINPTS_ID
 
Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm
DISTANCE_FUNCTION_ID
 
Constructor Summary
HiCO(PCABasedCorrelationDistanceFunction distanceFunction, int mu)
          Constructor.
 
Method Summary
protected  Logging getLogger()
          Get the (STATIC) logger for this class.
 
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS
expandClusterOrder, expandClusterOrderDouble, getDistanceFactory, getInputTypeRestriction, getMinPts, run
 
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm
getDistanceFunction
 
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.OPTICSTypeAlgorithm
run
 

Field Detail

logger

private static final Logging logger
The logger for this class.


MU_ID

public static final OptionID MU_ID
Parameter to specify the smoothing factor, must be an integer greater than 0. The {link MU_ID-nearest neighbor is used to compute the correlation reachability of an object.

Key: -hico.mu


K_ID

public static final OptionID K_ID
Optional parameter to specify the number of nearest neighbors considered in the PCA, must be an integer greater than 0. If this parameter is not set, k is set to the value of MU_ID.

Key: -hico.k

Default value: MU_ID


DELTA_ID

public static final OptionID DELTA_ID
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: -hico.delta


ALPHA_ID

public static final OptionID ALPHA_ID
The threshold for 'strong' eigenvectors: the 'strong' eigenvectors explain a portion of at least alpha of the total variance.

Default value: DEFAULT_ALPHA

Key: -hico.alpha


DEFAULT_DELTA

public static final double DEFAULT_DELTA
The default value for DELTA_ID.

See Also:
Constant Field Values

DEFAULT_ALPHA

public static final double DEFAULT_ALPHA
The default value for ALPHA_ID.

See Also:
Constant Field Values
Constructor Detail

HiCO

public HiCO(PCABasedCorrelationDistanceFunction distanceFunction,
            int mu)
Constructor.

Parameters:
distanceFunction - Distance function
mu - Mu parameter
Method Detail

getLogger

protected Logging getLogger()
Description copied from class: AbstractAlgorithm
Get the (STATIC) logger for this class.

Overrides:
getLogger in class OPTICS<V extends NumberVector<V,?>,PCACorrelationDistance>
Returns:
the static logger

Release 0.4.0 (2011-09-20_1324)