de.lmu.ifi.dbs.elki.algorithm.outlier.clustering

Class CBLOF.Parameterizer<O extends NumberVector>

java.lang.Object

de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer

de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.CBLOF.Parameterizer<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Parameterizer

Enclosing class:

CBLOF<O extends NumberVector>

public static class CBLOF.Parameterizer<O extends NumberVector>
extends AbstractParameterizer

Parameterization class.

Author:

Patrick Kostjens

Field Summary

Fields

Modifier and Type	Field and Description
protected double	alpha The ratio of the size that separates the large clusters from the small clusters.
static OptionID	ALPHPA_ID Parameter to specify the alpha value to be used by the algorithm.
protected double	beta The minimal ratio between two consecutive clusters (when ordered descending by size) at which the boundary between the large and small clusters is set.
static OptionID	BETA_ID Parameter to specify the beta value to be used by the algorithm.
static OptionID	CLUSTERING_ID Parameter to specify the algorithm to be used for clustering.
protected ClusteringAlgorithm<Clustering<MeanModel>>	clusteringAlgorithm The clustering algorithm to use.
protected NumberVectorDistanceFunction<? super O>	distance Distance function to use.

Constructor Summary

Constructors

Constructor and Description
Parameterizer()

Method Summary

Modifier and Type	Method and Description
protected CBLOF<O>	makeInstance() Make an instance after successful configuration.
protected void	makeOptions(Parameterization config) Add all options.

Methods inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer

configure, make

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

CLUSTERING_ID

public static final OptionID CLUSTERING_ID

Parameter to specify the algorithm to be used for clustering.

ALPHPA_ID

public static final OptionID ALPHPA_ID

Parameter to specify the alpha value to be used by the algorithm.

BETA_ID

public static final OptionID BETA_ID

Parameter to specify the beta value to be used by the algorithm.

clusteringAlgorithm

protected ClusteringAlgorithm<Clustering<MeanModel>> clusteringAlgorithm

The clustering algorithm to use.

alpha

protected double alpha

The ratio of the size that separates the large clusters from the small clusters. The clusters are ordered descending by size and are taken until the specified ratio of the data is included. For example: a ratio of 0.9 indicates that the large clusters should cover at least 90% of the data points.

beta

protected double beta

The minimal ratio between two consecutive clusters (when ordered descending by size) at which the boundary between the large and small clusters is set. For example: a ratio of 3 means that the clusters are separated between cluster i and (i+1) (where (i+1) is the first cluster smaller than i) when cluster i is at least 3 times bigger than (i+1).

distance

protected NumberVectorDistanceFunction<? super O extends NumberVector> distance

Distance function to use.

Constructor Detail

Parameterizer

public Parameterizer()

Method Detail

makeOptions

protected void makeOptions(Parameterization config)

Description copied from class: AbstractParameterizer

Add all options. ALWAYS call super.makeOptions(config), unless you have a strong reason to do otherwise!

Overrides:

makeOptions in class AbstractParameterizer

Parameters:

config - Parameterization to add options to.

makeInstance

protected CBLOF<O> makeInstance()

Description copied from class: AbstractParameterizer

Make an instance after successful configuration.

Specified by:

makeInstance in class AbstractParameterizer

Returns:

instance