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

Class ExtractFlatClusteringFromHierarchy.Parameterizer<D extends Distance<D>>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.ExtractFlatClusteringFromHierarchy.Parameterizer<D>

All Implemented Interfaces:

Parameterizer

Enclosing class:

ExtractFlatClusteringFromHierarchy<D extends Distance<D>>

public static class ExtractFlatClusteringFromHierarchy.Parameterizer<D extends Distance<D>>
extends AbstractParameterizer

Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
(package private) HierarchicalClusteringAlgorithm<D>	algorithm The hierarchical clustering algorithm to run.
(package private) int	minclusters Number of clusters to extract.
static OptionID	MINCLUSTERS_ID The minimum number of clusters to extract.
static OptionID	MODE_ID Extraction mode to use.
(package private) ExtractFlatClusteringFromHierarchy.OutputMode	outputmode Flag to produce empty clusters to model the hierarchy above.
static OptionID	OUTPUTMODE_ID Parameter to configure the output mode (nested or truncated clusters).
(package private) boolean	singletons Also create singleton clusters.
static OptionID	SINGLETONS_ID Flag to produce singleton clusters.
(package private) D	threshold Threshold level.
static OptionID	THRESHOLD_ID The threshold level for which to extract the clustering.
(package private) ExtractFlatClusteringFromHierarchy.ThresholdMode	thresholdmode Threshold mode.

Constructor Summary

Constructors

Constructor and Description
ExtractFlatClusteringFromHierarchy.Parameterizer()

Method Summary

Methods

Modifier and Type	Method and Description
protected ExtractFlatClusteringFromHierarchy<D>	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

MODE_ID

public static final OptionID MODE_ID

Extraction mode to use.

MINCLUSTERS_ID

public static final OptionID MINCLUSTERS_ID

The minimum number of clusters to extract.

THRESHOLD_ID

public static final OptionID THRESHOLD_ID

The threshold level for which to extract the clustering.

OUTPUTMODE_ID

public static final OptionID OUTPUTMODE_ID

Parameter to configure the output mode (nested or truncated clusters).

SINGLETONS_ID

public static final OptionID SINGLETONS_ID

Flag to produce singleton clusters.

minclusters

int minclusters

Number of clusters to extract.

threshold

D extends Distance<D> threshold

Threshold level.

outputmode

ExtractFlatClusteringFromHierarchy.OutputMode outputmode

Flag to produce empty clusters to model the hierarchy above.

algorithm

HierarchicalClusteringAlgorithm<D extends Distance<D>> algorithm

The hierarchical clustering algorithm to run.

thresholdmode

ExtractFlatClusteringFromHierarchy.ThresholdMode thresholdmode

Threshold mode.

singletons

boolean singletons

Also create singleton clusters.

Constructor Detail

ExtractFlatClusteringFromHierarchy.Parameterizer

public ExtractFlatClusteringFromHierarchy.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 ExtractFlatClusteringFromHierarchy<D> makeInstance()

Description copied from class: AbstractParameterizer

Make an instance after successful configuration.

Specified by:

makeInstance in class AbstractParameterizer

Returns:

instance