magpie.data.utilities.normalizers

Class InverseNormalizer

java.lang.Object

magpie.data.utilities.normalizers.BaseDatasetNormalizer

magpie.data.utilities.normalizers.InverseNormalizer

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Commandable, Options, Printable

public class InverseNormalizer
extends BaseDatasetNormalizer

Invert the attributes. Here, I'm defining 1 / 0 = 0 to avoid numerical problems. If you're using this on attributes that could be zero, don't blame the author.

This class was originally used to normalize data that lies on an exponential distribution.

Usage: <scale>
scale: Typical scale of distribution

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
InverseNormalizer()

Method Summary

Modifier and Type	Method and Description
double	getScale() Get scale factor used when inverting data
protected void	normalizeAttributes(Dataset Data) Perform the actual normalization on the attributes
protected void	normalizeClassVariable(Dataset Data) Perform the actual normalization on the class variable.
java.lang.String	printUsage() Print out required format for options.
protected void	restoreAttributes(Dataset Data) Perform the actual restoration on the attributes
protected void	restoreClassVariable(Dataset Data) Perform the actual restoration on the class variables (measured and predicted!)
void	setOptions(java.util.List<java.lang.Object> Options) Set any options for this object.
void	setScale(double s) Define scale of attributes / class.
protected void	trainOnAttributes(Dataset Data) Perform the actual training work for attributes.
protected void	trainOnMeasuredClass(Dataset Data) Perform the actual training work for the class variable.

Methods inherited from class magpie.data.utilities.normalizers.BaseDatasetNormalizer

about, clone, isTrained, normalize, printCommand, printDescription, restore, runCommand, setToNormalizeAttributes, setToNormalizeClass, test, train, willNormalizeAttributes, willNormalizeClass

Methods inherited from class java.lang.Object

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

Constructor Detail

InverseNormalizer

public InverseNormalizer()

Method Detail

setOptions

public void setOptions(java.util.List<java.lang.Object> Options)
                throws java.lang.Exception

Description copied from interface: Options

Set any options for this object. If parsing the options fails, return an Exception with the usage as its message.

Parameters:

Options - Array of options as Objects - can be null

Throws:

java.lang.Exception - if problem with inputs

printUsage

public java.lang.String printUsage()

Description copied from interface: Options

Print out required format for options. For consistency, should start with "Usage: ".

Returns:

Usage for this function

setScale

public void setScale(double s)

Define scale of attributes / class. Inverse will be Scale / x.

Parameters:

s - Desired scale factor

getScale

public double getScale()

Get scale factor used when inverting data

Returns:

Scale factor

trainOnMeasuredClass

protected void trainOnMeasuredClass(Dataset Data)

Description copied from class: BaseDatasetNormalizer

Perform the actual training work for the class variable. Must establish the parameters necessary to normalize attributes and return them to their original range.

NOTE: Use the measured class variable to train normalizer.

Specified by:

trainOnMeasuredClass in class BaseDatasetNormalizer

Parameters:

Data - Training set

trainOnAttributes

protected void trainOnAttributes(Dataset Data)

Description copied from class: BaseDatasetNormalizer

Perform the actual training work for attributes. Must establish the parameters necessary to normalize attributes and return them to their original range.

Specified by:

trainOnAttributes in class BaseDatasetNormalizer

Parameters:

Data - Training set

normalizeAttributes

protected void normalizeAttributes(Dataset Data)

Description copied from class: BaseDatasetNormalizer

Perform the actual normalization on the attributes

Specified by:

normalizeAttributes in class BaseDatasetNormalizer

Parameters:

Data - Dataset to be transformed

restoreAttributes

protected void restoreAttributes(Dataset Data)

Description copied from class: BaseDatasetNormalizer

Perform the actual restoration on the attributes

Specified by:

restoreAttributes in class BaseDatasetNormalizer

Parameters:

Data - Dataset to be transformed

normalizeClassVariable

protected void normalizeClassVariable(Dataset Data)

Description copied from class: BaseDatasetNormalizer

Perform the actual normalization on the class variable. Predicted and measured class variables must be transformed the same way

Specified by:

normalizeClassVariable in class BaseDatasetNormalizer

Parameters:

Data - Dataset to be transformed

restoreClassVariable

protected void restoreClassVariable(Dataset Data)

Description copied from class: BaseDatasetNormalizer

Perform the actual restoration on the class variables (measured and predicted!)

Specified by:

restoreClassVariable in class BaseDatasetNormalizer

Parameters:

Data - Dataset to be transformed