de.lmu.ifi.dbs.elki.datasource.filter
Class AttributeWiseMinMaxNormalization<V extends NumberVector<V,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.datasource.filter.AbstractConversionFilter<O,O>
      de.lmu.ifi.dbs.elki.datasource.filter.AbstractNormalization<V>
          de.lmu.ifi.dbs.elki.datasource.filter.AttributeWiseMinMaxNormalization<V>

Type Parameters:

V - vector type

All Implemented Interfaces:

Normalization<V>, ObjectFilter, InspectionUtilFrequentlyScanned, Parameterizable

public class AttributeWiseMinMaxNormalization<V extends NumberVector<V,?>>
extends AbstractNormalization<V>

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

Nested Class Summary

static class

AttributeWiseMinMaxNormalization.Parameterizer<V extends NumberVector<V,?>> Parameterization class.

Field Summary

private double[]	maxima Stores the maximum in each dimension.
static OptionID	MAXIMA_ID Parameter for maximum.
private double[]	minima Stores the minimum in each dimension.
static OptionID	MINIMA_ID Parameter for minimum.

Constructor Summary

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

Method Summary

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 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.AbstractNormalization

convertedType, normalizeObjects

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

MINIMA_ID

public static final OptionID MINIMA_ID

Parameter for minimum.

MAXIMA_ID

public static final OptionID MAXIMA_ID

Parameter for maximum.

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,?>,V extends NumberVector<V,?>>

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,?>,V extends NumberVector<V,?>>

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,?>,V extends NumberVector<V,?>>

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.

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<V,?>>

Overrides:

transform in class AbstractNormalization<V extends NumberVector<V,?>>

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<V,?>>

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,?>,V extends NumberVector<V,?>>

Returns:

Type restriction