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

Class KMeansMinusMinus.Parameterizer<V extends NumberVector>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.AbstractNumberVectorDistanceBasedAlgorithm.Parameterizer<V>

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans.Parameterizer<V>

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansMinusMinus.Parameterizer<V>

All Implemented Interfaces:

Parameterizer

Enclosing class:

KMeansMinusMinus<V extends NumberVector>

public static class KMeansMinusMinus.Parameterizer<V extends NumberVector>
extends AbstractKMeans.Parameterizer<V>

Parameterization class.

Author:

Jonas Steinke

Field Summary

Fields

Modifier and Type	Field and Description
static OptionID	NOISE_FLAG_ID Flag to produce a "noise" cluster, instead of assigning them to the nearest neighbor.
private boolean	noiseFlag Noise cluster flag.
private double	rate Outlier rate.
static OptionID	RATE_ID Parameter to specify the number of neighbors to ignore.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans.Parameterizer

initializer, k, maxiter, varstat

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractNumberVectorDistanceBasedAlgorithm.Parameterizer

distanceFunction

Constructor Summary

Constructors

Constructor and Description
Parameterizer()

Method Summary

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

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans.Parameterizer

getParameterDistanceFunction, getParameterInitialization, getParameterK, getParameterMaxIter, getParameterVarstat, needsMetric

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

RATE_ID

public static final OptionID RATE_ID

Parameter to specify the number of neighbors to ignore.

NOISE_FLAG_ID

public static final OptionID NOISE_FLAG_ID

Flag to produce a "noise" cluster, instead of assigning them to the nearest neighbor.

rate

private double rate

Outlier rate.

noiseFlag

private boolean noiseFlag

Noise cluster flag.

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 AbstractKMeans.Parameterizer<V extends NumberVector>

Parameters:

config - Parameterization to add options to.

makeInstance

protected KMeansMinusMinus<V> makeInstance()

Description copied from class: AbstractParameterizer

Make an instance after successful configuration.

Specified by:

makeInstance in class AbstractKMeans.Parameterizer<V extends NumberVector>

Returns:

instance