Package elki.datasource.filter.normalization.columnwise

Class AttributeWiseBetaNormalization<V extends NumberVector>

java.lang.Object

elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization<V>

elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization<V>

Type Parameters:

V - vector type

All Implemented Interfaces:

Normalization<V>, ObjectFilter

public class AttributeWiseBetaNormalization<V extends NumberVector>
extends AttributeWiseCDFNormalization<V>

Project the data using a Beta distribution.

This is a crude heuristic, that may or may not work for your data set. There currently is no theoretical foundation of why it may be sensible or not to do this.

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	AttributeWiseBetaNormalization.Par<V extends NumberVector>	Parameterization class.

Field Summary

Fields

Modifier and Type	Field	Description
protected double	alpha	Expected outlier rate alpha.
protected NumberVector.Factory<V>	factory	Number vector factory.
private static Logging	LOG	Class logger.

Fields inherited from class elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization

dists, estimators

Constructor Summary

Constructors

Constructor	Description
AttributeWiseBetaNormalization(java.util.List<? extends DistributionEstimator<?>> estimators, double alpha)	Constructor.

Method Summary

Modifier and Type	Method	Description
MultipleObjectsBundle	filter(MultipleObjectsBundle objects)	Filter a set of object packages.
V	restore(V featureVector)	Transforms a feature vector to the original attribute ranges.
LinearEquationSystem	transform(LinearEquationSystem linearEquationSystem)	Transforms a linear equation system describing linear dependencies derived on the normalized space into a linear equation system describing linear dependencies quantitatively adapted to the original space.

Methods inherited from class elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization

constantZero, findBestFit, toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

LOG

private static final Logging LOG

Class logger.

factory

protected NumberVector.Factory<V extends NumberVector> factory

Number vector factory.

alpha

protected double alpha

Expected outlier rate alpha.

Constructor Detail

AttributeWiseBetaNormalization

public AttributeWiseBetaNormalization(java.util.List<? extends DistributionEstimator<?>> estimators,
                                      double alpha)

Constructor.

Parameters:

estimators - Distribution estimators

Method Detail

filter

public MultipleObjectsBundle filter(MultipleObjectsBundle objects)

Description copied from interface: ObjectFilter

Filter a set of object packages.

Specified by:

filter in interface ObjectFilter

Overrides:

filter in class AttributeWiseCDFNormalization<V extends NumberVector>

Parameters:

objects - Object to filter

Returns:

Filtered objects

restore

public V restore(V featureVector)
          throws NonNumericFeaturesException

Description copied from interface: Normalization

Transforms a feature vector to the original attribute ranges.

Parameters:

featureVector - a feature vector to be transformed into original space

Returns:

a feature vector transformed into original space corresponding to the given feature vector

Throws:

NonNumericFeaturesException - feature vector is not compatible with values initialized during normalization

transform

public LinearEquationSystem transform(LinearEquationSystem linearEquationSystem)

Description copied from interface: Normalization

Transforms a linear equation system describing linear dependencies derived on the normalized space into a linear equation system describing linear dependencies quantitatively adapted to the original space.

Parameters:

linearEquationSystem - the linear equation system to be transformed

Returns:

a linear equation system describing linear dependencies derived on the normalized space transformed into a linear equation system describing linear dependencies quantitatively adapted to the original space