gov.sandia.cognition.learning.data.feature

Class StandardDistributionNormalizer

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.math.AbstractScalarFunction<java.lang.Double>

gov.sandia.cognition.math.AbstractUnivariateScalarFunction

gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer

All Implemented Interfaces:

Evaluator<java.lang.Double,java.lang.Double>, ScalarFunction<java.lang.Double>, UnivariateScalarFunction, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

@CodeReview(reviewer="Kevin R. Dixon",
            date="2009-07-06",
            changesNeeded=false,
            comments={"Made the learning methods take <? extends Number>","Now extends AbstractUnivariateScalarFunction","Cleaned up javadoc"})
public class StandardDistributionNormalizer
extends AbstractUnivariateScalarFunction

The StandardDistributionNormalizer class implements a normalization method where a real value is converted onto a standard distribution. This means that the value is subtracted by the mean and divided by the standard deviation.

f(x) = (x - mean) / (standardDeviation)

Since:

2.0

Author:

Justin Basilico

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	StandardDistributionNormalizer.Learner The Learner class implements a BatchLearner object for a StandardDistributionNormalizer.

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_MEAN The default mean is 0.0.
static double	DEFAULT_VARIANCE The default variance is 1.0.
protected double	mean The mean of normalization.
protected double	standardDeviation The cached value of the standard deviation for normalization.
protected double	variance The variance for normalization.

Constructor Summary

Constructors

Constructor and Description
StandardDistributionNormalizer() Creates a new instance of StandardNormalization with a mean of 0.0 and a variance of 1.0.
StandardDistributionNormalizer(double mean, double variance) Creates a new instance of StandardDistributionNormalizer with the given mean and variance.
StandardDistributionNormalizer(StandardDistributionNormalizer other) Creates a new copy of a StandardDistributionNormalizer.
StandardDistributionNormalizer(UnivariateGaussian gaussian) Creates a new instance of StandardDistributionNormalizer from the given Gaussian.

Method Summary

Modifier and Type	Method and Description
StandardDistributionNormalizer	clone() Creates a new copy of this StandardDistributionNormalizer.
double	evaluate(double value) Normalizes the given double value by subtracting the mean and dividing by the standard deviation (the square root of the variance).
double	getMean() Gets the mean.
double	getVariance() Gets the variance.
static StandardDistributionNormalizer	learn(java.util.Collection<? extends java.lang.Number> values) Builds a StandardDistributionNormalizer by computing the mean and variance of the given collection of values.
static StandardDistributionNormalizer	learn(java.util.Collection<? extends java.lang.Number> values, double outlierPercent) Builds a StandardDistributionNormalizer by computing the mean and variance of the given collection of values.
void	setMean(double mean) Sets the mean.
void	setVariance(double variance) Sets the variance.

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.math.UnivariateScalarFunction

evaluate, evaluateAsDouble

Field Detail

DEFAULT_MEAN

public static final double DEFAULT_MEAN

The default mean is 0.0.

See Also:

Constant Field Values

DEFAULT_VARIANCE

public static final double DEFAULT_VARIANCE

The default variance is 1.0. This means that by default there is no normalization by variance.

See Also:

Constant Field Values

mean

protected double mean

The mean of normalization.

variance

protected double variance

The variance for normalization.

standardDeviation

protected double standardDeviation

The cached value of the standard deviation for normalization.

Constructor Detail

StandardDistributionNormalizer

public StandardDistributionNormalizer()

Creates a new instance of StandardNormalization with a mean of 0.0 and a variance of 1.0.

StandardDistributionNormalizer

public StandardDistributionNormalizer(double mean,
                                      double variance)

Creates a new instance of StandardDistributionNormalizer with the given mean and variance.

Parameters:

mean - The mean.

variance - The variance.

StandardDistributionNormalizer

public StandardDistributionNormalizer(UnivariateGaussian gaussian)

Creates a new instance of StandardDistributionNormalizer from the given Gaussian.

Parameters:

gaussian - The Gaussian to initialize the normalizer with.

StandardDistributionNormalizer

public StandardDistributionNormalizer(StandardDistributionNormalizer other)

Creates a new copy of a StandardDistributionNormalizer.

Parameters:

other - The StandardDistributionNormalizer to copy.

Method Detail

clone

public StandardDistributionNormalizer clone()

Creates a new copy of this StandardDistributionNormalizer.

Specified by:

clone in interface CloneableSerializable

Overrides:

clone in class AbstractCloneableSerializable

Returns:

A new copy of this StandardDistributionNormalizer.

evaluate

public double evaluate(double value)

Normalizes the given double value by subtracting the mean and dividing by the standard deviation (the square root of the variance).

Parameters:

value - The value to normalize.

Returns:

The normalized value.

getMean

public double getMean()

Gets the mean.

Returns:

The mean.

setMean

public void setMean(double mean)

Sets the mean.

Parameters:

mean - The mean.

getVariance

public double getVariance()

Gets the variance.

Returns:

The variance.

setVariance

public void setVariance(double variance)

Sets the variance. It must be greater than 0.0.

Parameters:

variance - The variance.

learn

public static StandardDistributionNormalizer learn(java.util.Collection<? extends java.lang.Number> values)

Builds a StandardDistributionNormalizer by computing the mean and variance of the given collection of values.

Parameters:

values - The values to use to build the normalizer.

Returns:

The StandardDistributionNormalizer created from the mean and variance of the given values.

learn

public static StandardDistributionNormalizer learn(java.util.Collection<? extends java.lang.Number> values,
                                                   double outlierPercent)

Builds a StandardDistributionNormalizer by computing the mean and variance of the given collection of values. It will exclude the given percentage of outliers from the value.

Parameters:

values - The values to use to build the normalizer.

outlierPercent - The percentage of outliers to exclude.

Returns:

The StandardDistributionNormalizer created from the mean and variance of the given values.