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

Class SUBCLU.Parameterizer<V extends NumberVector>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.SUBCLU.Parameterizer<V>

All Implemented Interfaces:

Parameterizer

Enclosing class:

SUBCLU<V extends NumberVector>

public static class SUBCLU.Parameterizer<V extends NumberVector>
extends AbstractParameterizer

Parameterization class.

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field and Description
protected DimensionSelectingSubspaceDistanceFunction<V>	distance The distance function to determine the distance between objects.
static OptionID	DISTANCE_FUNCTION_ID The distance function to determine the distance between objects.
protected double	epsilon Maximum radius of the neighborhood to be considered.
static OptionID	EPSILON_ID Maximum radius of the neighborhood to be considered.
protected int	mindim Minimum dimensionality.
static OptionID	MINDIM_ID Minimum dimensionality to generate clusters.
protected int	minpts Minimum number of points.
static OptionID	MINPTS_ID Parameter to specify the threshold for minimum number of points in the epsilon-neighborhood of a point, must be an integer greater than 0.

Constructor Summary

Constructors

Constructor and Description
Parameterizer()

Method Summary

Modifier and Type	Method and Description
protected SUBCLU<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.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

DISTANCE_FUNCTION_ID

public static final OptionID DISTANCE_FUNCTION_ID

The distance function to determine the distance between objects.

EPSILON_ID

public static final OptionID EPSILON_ID

Maximum radius of the neighborhood to be considered.

MINPTS_ID

public static final OptionID MINPTS_ID

Parameter to specify the threshold for minimum number of points in the epsilon-neighborhood of a point, must be an integer greater than 0.

MINDIM_ID

public static final OptionID MINDIM_ID

Minimum dimensionality to generate clusters.

distance

protected DimensionSelectingSubspaceDistanceFunction<V extends NumberVector> distance

The distance function to determine the distance between objects.

epsilon

protected double epsilon

Maximum radius of the neighborhood to be considered.

minpts

protected int minpts

Minimum number of points.

mindim

protected int mindim

Minimum dimensionality.

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 SUBCLU<V> makeInstance()

Description copied from class: AbstractParameterizer

Make an instance after successful configuration.

Specified by:

makeInstance in class AbstractParameterizer

Returns:

instance