Package elki.clustering.uncertain

Class RepresentativeUncertainClustering.Par

java.lang.Object

elki.clustering.uncertain.RepresentativeUncertainClustering.Par

All Implemented Interfaces:

Parameterizer

Enclosing class:

RepresentativeUncertainClustering

public static class RepresentativeUncertainClustering.Par
extends java.lang.Object
implements Parameterizer

Parameterization class.

Author:

Alexander Koos, Erich Schubert

Field Summary

Fields

Modifier and Type	Field	Description
static OptionID	ALGORITHM_ID	Parameter to hand an algorithm to be wrapped and run to our instance of RepresentativeUncertainClustering.
protected double	alpha	Alpha parameter for confidence.
static OptionID	ALPHA_ID	Alpha parameter for confidence estimation.
static OptionID	CLUSTERDISTANCE_ID	Distance function to measure the similarity of clusterings.
static int	DEFAULT_ENSEMBLE_DEPTH	Default number of clusterings to run.
protected ClusteringDistanceSimilarity	distance	Distance (dissimilarity) for clusterinogs.
protected boolean	keep	Keep all samples (not only the representative results).
static OptionID	KEEP_SAMPLES_ID	Flag to keep all samples.
static OptionID	META_ALGORITHM_ID	Parameter to hand an algorithm for creating the meta-clustering to our instance of RepresentativeUncertainClustering.
protected ClusteringAlgorithm<?>	metaAlgorithm	Field to store the inner algorithm for meta-clustering
protected int	numsamples	Field to store parameter the number of samples.
protected RandomFactory	random	Random factory for sampling.
static OptionID	RANDOM_ID	Parameter to specify the random generator.
static OptionID	SAMPLES_ID	Parameter to specify the amount of clusterings that shall be created and compared.
protected ClusteringAlgorithm<?>	samplesAlgorithm	Field to store the algorithm.

Constructor Summary

Constructors

Constructor	Description
Par()

Method Summary

Modifier and Type	Method	Description
void	configure(Parameterization config)	Configure the class.
RepresentativeUncertainClustering	make()	Make an instance after successful configuration.

Methods inherited from class java.lang.Object

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

Field Detail

DEFAULT_ENSEMBLE_DEPTH

public static final int DEFAULT_ENSEMBLE_DEPTH

Default number of clusterings to run.

See Also:

Constant Field Values

CLUSTERDISTANCE_ID

public static final OptionID CLUSTERDISTANCE_ID

Distance function to measure the similarity of clusterings.

META_ALGORITHM_ID

public static final OptionID META_ALGORITHM_ID

Parameter to hand an algorithm for creating the meta-clustering to our instance of RepresentativeUncertainClustering.

It has to use a metric distance function to work on the sample-clusterings.

ALGORITHM_ID

public static final OptionID ALGORITHM_ID

Parameter to hand an algorithm to be wrapped and run to our instance of RepresentativeUncertainClustering.

SAMPLES_ID

public static final OptionID SAMPLES_ID

Parameter to specify the amount of clusterings that shall be created and compared.

KEEP_SAMPLES_ID

public static final OptionID KEEP_SAMPLES_ID

Flag to keep all samples.

RANDOM_ID

public static final OptionID RANDOM_ID

Parameter to specify the random generator.

ALPHA_ID

public static final OptionID ALPHA_ID

Alpha parameter for confidence estimation.

distance

protected ClusteringDistanceSimilarity distance

Distance (dissimilarity) for clusterinogs.

metaAlgorithm

protected ClusteringAlgorithm<?> metaAlgorithm

Field to store the inner algorithm for meta-clustering

samplesAlgorithm

protected ClusteringAlgorithm<?> samplesAlgorithm

Field to store the algorithm.

numsamples

protected int numsamples

Field to store parameter the number of samples.

random

protected RandomFactory random

Random factory for sampling.

alpha

protected double alpha

Alpha parameter for confidence.

keep

protected boolean keep

Keep all samples (not only the representative results).

Constructor Detail

Par

public Par()

Method Detail

configure

public void configure(Parameterization config)

Description copied from interface: Parameterizer

Configure the class.

Note: the status is collected by the parameterization object, so that multiple errors may arise and be reported in one run.

Specified by:

configure in interface Parameterizer

Parameters:

config - Parameterization

make

public RepresentativeUncertainClustering make()

Description copied from interface: Parameterizer

Make an instance after successful configuration.

Note: your class should return the exact type, only this very broad interface should use Object as return type.

Specified by:

make in interface Parameterizer

Returns:

a new instance