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

Class SampleKMeansInitialization.Parameterizer<V extends NumberVector<?>,D extends Distance<?>>

java.lang.Object

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

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

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.SampleKMeansInitialization.Parameterizer<V,D>

Type Parameters:

V - Vector type

D - Distance type

All Implemented Interfaces:

Parameterizer

Enclosing class:

SampleKMeansInitialization<V extends NumberVector<?>,D extends Distance<?>>

public static class SampleKMeansInitialization.Parameterizer<V extends NumberVector<?>,D extends Distance<?>>
extends AbstractKMeansInitialization.Parameterizer<V>

Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
protected KMeans<V,D,?>	innerkMeans Inner k-means algorithm to use.
static OptionID	KMEANS_ID Parameter to specify the kMeans variant.
protected double	rate Sampling rate.
static OptionID	SAMPLE_ID Parameter to specify the sampling rate.

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

rnd

Constructor Summary

Constructors

Constructor and Description
SampleKMeansInitialization.Parameterizer()

Method Summary

Methods

Modifier and Type	Method and Description
protected SampleKMeansInitialization<V,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

KMEANS_ID

public static final OptionID KMEANS_ID

Parameter to specify the kMeans variant.

SAMPLE_ID

public static final OptionID SAMPLE_ID

Parameter to specify the sampling rate.

innerkMeans

protected KMeans<V extends NumberVector<?>,D extends Distance<?>,?> innerkMeans

Inner k-means algorithm to use.

rate

protected double rate

Sampling rate.

Constructor Detail

SampleKMeansInitialization.Parameterizer

public SampleKMeansInitialization.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 AbstractKMeansInitialization.Parameterizer<V extends NumberVector<?>>

Parameters:

config - Parameterization to add options to.

makeInstance

protected SampleKMeansInitialization<V,D> makeInstance()

Description copied from class: AbstractParameterizer

Make an instance after successful configuration.

Specified by:

makeInstance in class AbstractParameterizer

Returns:

instance