de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise

Class AttributeWiseMinMaxNormalization<V extends NumberVector>

java.lang.Object

de.lmu.ifi.dbs.elki.datasource.filter.AbstractConversionFilter<I,O>

de.lmu.ifi.dbs.elki.datasource.filter.AbstractVectorConversionFilter<V,V>

de.lmu.ifi.dbs.elki.datasource.filter.normalization.AbstractNormalization<V>

de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization<V>

Type Parameters:

V - vector type

All Implemented Interfaces:

Normalization<V>, ObjectFilter

@Alias(value={"de.lmu.ifi.dbs.elki.datasource.filter.normalization.AttributeWiseMinMaxNormalization","de.lmu.ifi.dbs.elki.datasource.filter.AttributeWiseMinMaxNormalization"})
public class AttributeWiseMinMaxNormalization<V extends NumberVector>
extends AbstractNormalization<V>

Class to perform and undo a normalization on real vectors with respect to given minimum and maximum in each dimension.

Since:

0.4.0

Author:

Elke Achtert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	AttributeWiseMinMaxNormalization.Parameterizer<V extends NumberVector> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private static Logging	LOG Class logger.
private double[]	maxima Stores the maximum in each dimension.
private double[]	minima Stores the minimum in each dimension.

Fields inherited from class de.lmu.ifi.dbs.elki.datasource.filter.AbstractVectorConversionFilter

factory

Constructor Summary

Constructors

Constructor and Description
AttributeWiseMinMaxNormalization(double[] minima, double[] maxima) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
private double	factor(int dimension) Returns a factor for normalization in a certain dimension.
protected V	filterSingleObject(V featureVector) Normalize a single instance.
protected SimpleTypeInformation<? super V>	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Class logger.
protected void	prepareProcessInstance(V featureVector) Process a single object during initialization.
protected boolean	prepareStart(SimpleTypeInformation<V> in) Return "true" when the normalization needs initialization (two-pass filtering!).
V	restore(V featureVector) Transforms a feature vector to the original attribute ranges.
String	toString()
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 de.lmu.ifi.dbs.elki.datasource.filter.normalization.AbstractNormalization

convertedType

Methods inherited from class de.lmu.ifi.dbs.elki.datasource.filter.AbstractVectorConversionFilter

initializeOutputType

Methods inherited from class de.lmu.ifi.dbs.elki.datasource.filter.AbstractConversionFilter

filter, prepareComplete

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.datasource.filter.ObjectFilter

filter

Field Detail

LOG

private static final Logging LOG

Class logger.

maxima

private double[] maxima

Stores the maximum in each dimension.

minima

private double[] minima

Stores the minimum in each dimension.

Constructor Detail

AttributeWiseMinMaxNormalization

public AttributeWiseMinMaxNormalization(double[] minima,
                                double[] maxima)

Constructor.

Parameters:

minima - Minimum values

maxima - Maximum values

Method Detail

prepareStart

protected boolean prepareStart(SimpleTypeInformation<V> in)

Description copied from class: AbstractConversionFilter

Return "true" when the normalization needs initialization (two-pass filtering!).

Overrides:

prepareStart in class AbstractConversionFilter<V extends NumberVector,V extends NumberVector>

Parameters:

in - Input type information

Returns:

true or false

prepareProcessInstance

protected void prepareProcessInstance(V featureVector)

Description copied from class: AbstractConversionFilter

Process a single object during initialization.

Overrides:

prepareProcessInstance in class AbstractConversionFilter<V extends NumberVector,V extends NumberVector>

Parameters:

featureVector - Object to process

filterSingleObject

protected V filterSingleObject(V featureVector)

Description copied from class: AbstractConversionFilter

Normalize a single instance. You can implement this as UnsupportedOperationException if you override both public "normalize" functions!

Specified by:

filterSingleObject in class AbstractConversionFilter<V extends NumberVector,V extends NumberVector>

Parameters:

featureVector - Database object to normalize

Returns:

Normalized database object

restore

public V restore(V featureVector)
                               throws NonNumericFeaturesException

Description copied from interface: Normalization

Transforms a feature vector to the original attribute ranges.

Specified by:

restore in interface Normalization<V extends NumberVector>

Overrides:

restore in class AbstractNormalization<V extends NumberVector>

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

factor

private double factor(int dimension)

Returns a factor for normalization in a certain dimension.

The provided factor is the maximum-minimum in the specified dimension, if these two values differ, otherwise it is the maximum if this value differs from 0, otherwise it is 1.

Parameters:

dimension - the dimension to get a factor for normalization

Returns:

a factor for normalization in a certain dimension

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.

Specified by:

transform in interface Normalization<V extends NumberVector>

Overrides:

transform in class AbstractNormalization<V extends NumberVector>

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

toString

public String toString()

Overrides:

toString in class AbstractNormalization<V extends NumberVector>

getLogger

protected Logging getLogger()

Description copied from class: AbstractConversionFilter

Class logger.

Specified by:

getLogger in class AbstractConversionFilter<V extends NumberVector,V extends NumberVector>

Returns:

Logger

getInputTypeRestriction

protected SimpleTypeInformation<? super V> getInputTypeRestriction()

Description copied from class: AbstractConversionFilter

Get the input type restriction used for negotiating the data query.

Specified by:

getInputTypeRestriction in class AbstractConversionFilter<V extends NumberVector,V extends NumberVector>

Returns:

Type restriction