Catalano.MachineLearning.FeatureScaling

Class Normalization

java.lang.Object

Catalano.MachineLearning.FeatureScaling.Normalization

All Implemented Interfaces:

IFeatureScaling, java.io.Serializable

public class Normalization
extends java.lang.Object
implements IFeatureScaling

Normalization data. Normalize in the specified given range.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Normalization() Initializes a new instance of the Normalization class.
Normalization(double min, double max) Initializes a new instance of the Normalization class.

Method Summary

Modifier and Type	Method and Description
double[][]	Apply(DecisionVariable[] variables, double[][] data) Apply the normalization.
double[][]	Apply(double[][] data) Apply the normalization.
void	ApplyInPlace(DecisionVariable[] attributes, double[][] data) Apply the normalization in place of the original data.
void	ApplyInPlace(double[][] data) Apply the normalization in place of the original data.
double[]	Compute(DecisionVariable[] attributes, double[] feature) Normalize the feature.
double[]	Compute(double[] feature) Normalize the feature.
double	getMax() Get maximum value.
double	getMin() Get minimum value.
double[][]	getRangeNormalization() Get range normalization.
void	setMax(double max) Set maximum value.
void	setMin(double min) Set minimum value.
void	setRangeNormalization(double[][] range) Set range normalization.

Methods inherited from class java.lang.Object

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

Constructor Detail

Normalization

public Normalization()

Initializes a new instance of the Normalization class.

Normalization

public Normalization(double min,
                     double max)

Initializes a new instance of the Normalization class.

Parameters:

min - Minimum value.

max - Maximum value.

Method Detail

getMin

public double getMin()

Get minimum value.

Returns:

Minimum value.

setMin

public void setMin(double min)

Set minimum value.

Parameters:

min - Minimum value.

getMax

public double getMax()

Get maximum value.

Returns:

Maximum value.

setMax

public void setMax(double max)

Set maximum value.

Parameters:

max - Maximum value.

getRangeNormalization

public double[][] getRangeNormalization()

Get range normalization.

Returns:

Range normalization.

setRangeNormalization

public void setRangeNormalization(double[][] range)

Set range normalization.

Parameters:

range - Range normalization.

Apply

public double[][] Apply(double[][] data)

Description copied from interface: IFeatureScaling

Apply the normalization.

Specified by:

Apply in interface IFeatureScaling

Parameters:

data - Data to be normalized.

Returns:

Normalized data.

Apply

public double[][] Apply(DecisionVariable[] variables,
                        double[][] data)

Description copied from interface: IFeatureScaling

Apply the normalization.

Specified by:

Apply in interface IFeatureScaling

Parameters:

variables - Decision variables.

data - Data to be normalized.

Returns:

Normalized. data.

ApplyInPlace

public void ApplyInPlace(double[][] data)

Description copied from interface: IFeatureScaling

Apply the normalization in place of the original data.

Specified by:

ApplyInPlace in interface IFeatureScaling

Parameters:

data - Data to be normalized.

ApplyInPlace

public void ApplyInPlace(DecisionVariable[] attributes,
                         double[][] data)

Description copied from interface: IFeatureScaling

Apply the normalization in place of the original data.

Specified by:

ApplyInPlace in interface IFeatureScaling

Parameters:

attributes - Decision variables.

data - Data to be normalized.

Compute

public double[] Compute(double[] feature)

Description copied from interface: IFeatureScaling

Normalize the feature.

Specified by:

Compute in interface IFeatureScaling

Parameters:

feature - Feature to be normalized.

Returns:

Normalized feature.

Compute

public double[] Compute(DecisionVariable[] attributes,
                        double[] feature)

Description copied from interface: IFeatureScaling

Normalize the feature.

Specified by:

Compute in interface IFeatureScaling

Parameters:

attributes - Decision variables.

feature - Feature.

Returns:

Normalized feature.