de.lmu.ifi.dbs.elki.normalization
Class AttributeWiseVarianceNormalization<V extends RealVector<V,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable
          de.lmu.ifi.dbs.elki.normalization.AbstractNormalization<V>
              de.lmu.ifi.dbs.elki.normalization.AttributeWiseVarianceNormalization<V>

Type Parameters:

V - vector type

All Implemented Interfaces:

Normalization<V>, Parameterizable

public class AttributeWiseVarianceNormalization<V extends RealVector<V,?>>
extends AbstractNormalization<V>

Class to perform and undo a normalization on real vectors with respect to given mean and standard deviation in each dimension.

Author:

Erich Schubert

Field Summary

private double[]	mean Stores the mean in each dimension.
static OptionID	MEAN_ID OptionID for MEAN_PARAM
private DoubleListParameter	MEAN_PARAM Parameter for means.
private double[]	stddev Stores the standard deviation in each dimension.
static OptionID	STDDEV_ID OptionID for STDDEV_PARAM
private DoubleListParameter	STDDEV_PARAM Parameter for stddevs.

Fields inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable

optionHandler

Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debug, logger

Constructor Summary

AttributeWiseVarianceNormalization()
Sets mean and stddev parameter to the optionhandler.

Method Summary

private void	determineMeanVariance(List<Pair<V,Associations>> objectAndAssociationsList) Determines the means and standard deviations in each dimension of the given featureVectors.
private void	determineMeanVariance(V[] featureVectors) Determines the mean and standard deviations in each dimension of the given featureVectors.
private double	normalize(int d, double val)
List<V>	normalize(List<V> featureVectors) Performs a normalization on a set of feature vectors.
List<Pair<V,Associations>>	normalizeObjects(List<Pair<V,Associations>> objectAndAssociationsList) Performs a normalization on a list of database objects and their associations.
private double	restore(int d, double val)
List<V>	restore(List<V> featureVectors) Transforms a set of feature vectores to the original attribute ranges.
V	restore(V featureVector) Transforms a feature vector to the original attribute ranges.
List<String>	setParameters(List<String> args) Sets the attributes of the class accordingly to the given parameters.
String	toString(String pre) Returns a string representation of this normalization.
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.normalization.AbstractNormalization

toString

Methods inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable

addOption, addParameterizable, addParameterizable, checkGlobalParameterConstraints, collectOptions, getAttributeSettings, getParameters, rememberParametersExcept, removeOption, removeParameterizable, shortDescription

Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debugFine, debugFiner, debugFinest, exception, progress, verbose, warning

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.utilities.optionhandling.Parameterizable

checkGlobalParameterConstraints, collectOptions, getParameters, shortDescription

Field Detail

MEAN_ID

public static final OptionID MEAN_ID

OptionID for MEAN_PARAM

STDDEV_ID

public static final OptionID STDDEV_ID

OptionID for STDDEV_PARAM

MEAN_PARAM

private final DoubleListParameter MEAN_PARAM

Parameter for means.

STDDEV_PARAM

private final DoubleListParameter STDDEV_PARAM

Parameter for stddevs.

mean

private double[] mean

Stores the mean in each dimension.

stddev

private double[] stddev

Stores the standard deviation in each dimension.

Constructor Detail

AttributeWiseVarianceNormalization

public AttributeWiseVarianceNormalization()

Sets mean and stddev parameter to the optionhandler.

Method Detail

normalize

private double normalize(int d,
                         double val)

restore

private double restore(int d,
                       double val)

normalizeObjects

public List<Pair<V,Associations>> normalizeObjects(List<Pair<V,Associations>> objectAndAssociationsList)
                                                                    throws NonNumericFeaturesException

Description copied from interface: Normalization

Performs a normalization on a list of database objects and their associations.

Parameters:

objectAndAssociationsList - the list of database objects and their associations

Returns:

a list of normalized database objects and their associations corresponding to the given list

Throws:

NonNumericFeaturesException - if feature vectors differ in length or values are not suitable to normalization

normalize

public List<V> normalize(List<V> featureVectors)
                                          throws NonNumericFeaturesException

Description copied from interface: Normalization

Performs a normalization on a set of feature vectors.

Parameters:

featureVectors - a set of feature vectors to be normalized

Returns:

a set of normalized feature vectors corresponding to the given feature vectors but being different objects

Throws:

NonNumericFeaturesException - if feature vectors differ in length or values are not suitable to normalization

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

restore

public List<V> restore(List<V> featureVectors)
                                        throws NonNumericFeaturesException

Description copied from interface: Normalization

Transforms a set of feature vectores to the original attribute ranges.

Parameters:

featureVectors - a set of feature vectors to be transformed into original space

Returns:

a set of feature vectors transformed into original space corresponding to the given feature vectors

Throws:

NonNumericFeaturesException - if feature vectors differ in length or are 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

toString

public String toString(String pre)

Returns a string representation of this normalization. The specified prefix pre will be the prefix of each new line. This method is used to write the parameters of a normalization to a result of an algorithm using this normalization.

Parameters:

pre - the prefix of each new line

Returns:

a string representation of this normalization

setParameters

public List<String> setParameters(List<String> args)
                           throws ParameterException

Sets the attributes of the class accordingly to the given parameters. Returns a new String array containing those entries of the given array that are neither expected nor used by this Parameterizable.

Specified by:

setParameters in interface Parameterizable

Overrides:

setParameters in class AbstractParameterizable

Parameters:

args - parameters to set the attributes accordingly to

Returns:

String[] an array containing the unused parameters

Throws:

IllegalArgumentException - in case of wrong parameter-setting

ParameterException - in case of wrong parameter-setting

determineMeanVariance

private void determineMeanVariance(V[] featureVectors)

Determines the mean and standard deviations in each dimension of the given featureVectors.

Parameters:

featureVectors - the list of feature vectors

determineMeanVariance

private void determineMeanVariance(List<Pair<V,Associations>> objectAndAssociationsList)

Determines the means and standard deviations in each dimension of the given featureVectors.

Parameters:

objectAndAssociationsList - the list of feature vectors and their associations