de.lmu.ifi.dbs.elki.algorithm.outlier

Class COP.Parameterizer<V extends NumberVector>

java.lang.Object

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

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

de.lmu.ifi.dbs.elki.algorithm.outlier.COP.Parameterizer<V>

All Implemented Interfaces:

Parameterizer

Enclosing class:

COP<V extends NumberVector>

public static class COP.Parameterizer<V extends NumberVector>
extends AbstractDistanceBasedAlgorithm.Parameterizer<V>

Parameterization class.

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field and Description
(package private) COP.DistanceDist	dist Distance distributution assumption.
static OptionID	DIST_ID Distribution assumption for distances.
(package private) double	expect Expected amount of outliers.
static OptionID	EXPECT_ID Expected share of outliers.
(package private) int	k Number of neighbors to be considered.
static OptionID	K_ID Parameter to specify the number of nearest neighbors of an object to be considered for computing its COP_SCORE, must be an integer greater than 0.
(package private) boolean	models Include COP models
static OptionID	MODELS_ID Include COP error vectors in output.
(package private) PCARunner	pca Holds the object performing the dependency derivation.
static OptionID	PCARUNNER_ID Class to compute the PCA with.

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

distanceFunction

Constructor Summary

Constructors

Constructor and Description
COP.Parameterizer()

Method Summary

Methods

Modifier and Type	Method and Description
protected COP<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

K_ID

public static final OptionID K_ID

Parameter to specify the number of nearest neighbors of an object to be considered for computing its COP_SCORE, must be an integer greater than 0.

Key: -cop.k

DIST_ID

public static final OptionID DIST_ID

Distribution assumption for distances.

Key: -cop.dist

PCARUNNER_ID

public static final OptionID PCARUNNER_ID

Class to compute the PCA with.

Key: -cop.pcarunner

EXPECT_ID

public static final OptionID EXPECT_ID

Expected share of outliers.

Key: -cop.expect Default: 0.001

MODELS_ID

public static final OptionID MODELS_ID

Include COP error vectors in output.

Key: -cop.models Default: off

k

int k

Number of neighbors to be considered.

pca

PCARunner pca

Holds the object performing the dependency derivation.

dist

COP.DistanceDist dist

Distance distributution assumption.

expect

double expect

Expected amount of outliers.

models

boolean models

Include COP models

Constructor Detail

COP.Parameterizer

public COP.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 AbstractDistanceBasedAlgorithm.Parameterizer<V extends NumberVector>

Parameters:

config - Parameterization to add options to.

makeInstance

protected COP<V> makeInstance()

Description copied from class: AbstractParameterizer

Make an instance after successful configuration.

Specified by:

makeInstance in class AbstractParameterizer

Returns:

instance