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Class weka.attributeSelection.PrincipalComponents

java.lang.Object
    |
    +----weka.attributeSelection.ASEvaluation
            |
            +----weka.attributeSelection.AttributeEvaluator
                    |
                    +----weka.attributeSelection.UnsupervisedAttributeEvaluator
                            |
                            +----weka.attributeSelection.PrincipalComponents

public class PrincipalComponents

extends UnsupervisedAttributeEvaluator

implements AttributeTransformer, OptionHandler

Valid options are:

-N
Don't normalize the input data.

-R
Retain enough pcs to account for this proportion of the variance.

-T
Transform through the PC space and back to the original space.

Version:

$Revision: 1.25 $

Author:

Mark Hall (mhall@cs.waikato.ac.nz)

Author:

Gabi Schmidberger (gabi@cs.waikato.ac.nz)

PrincipalComponents()

 

buildEvaluator(Instances)

Initializes principal components and performs the analysis

convertInstance(Instance)

Transform an instance in original (unormalized) format.

evaluateAttribute(int)

Evaluates the merit of a transformed attribute.

getNormalize()

Gets whether or not input data is to be normalized

getOptions()

Gets the current settings of PrincipalComponents

getTransformBackToOriginal()

Gets whether the data is to be transformed back to the original space.

getVarianceCovered()

Gets the proportion of total variance to account for when retaining principal components

globalInfo()

Returns a string describing this attribute transformer

listOptions()

Returns an enumeration describing the available options.

main(String[])

Main method for testing this class

normalizeTipText()

Returns the tip text for this property

setNormalize(boolean)

Set whether input data will be normalized.

setOptions(String[])

Parses a given list of options.

setTransformBackToOriginal(boolean)

Sets whether the data should be transformed back to the original space

setVarianceCovered(double)

Sets the amount of variance to account for when retaining principal components

toString()

Returns a description of this attribute transformer

transformBackToOriginalTipText()

Returns the tip text for this property

transformedData()

Gets the transformed training data.

transformedHeader()

Returns just the header for the transformed data (ie.

varianceCoveredTipText()

Returns the tip text for this property

public PrincipalComponents()

public java.lang.String globalInfo()

          Returns a string describing this attribute transformer

Returns:

a description of the evaluator suitable for displaying in the explorer/experimenter gui

public java.util.Enumeration listOptions()

          Returns an enumeration describing the available options.

Returns:

an enumeration of all the available options.

public void setOptions(java.lang.String options[]) throws java.lang.Exception

          Parses a given list of options. Valid options are:

-N
Don't normalize the input data.

-R
Retain enough pcs to account for this proportion of the variance.

-T
Transform through the PC space and back to the original space.

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

public java.lang.String normalizeTipText()

          Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

public void setNormalize(boolean n)

          Set whether input data will be normalized.

Parameters:

n - true if input data is to be normalized

public boolean getNormalize()

          Gets whether or not input data is to be normalized

Returns:

true if input data is to be normalized

public java.lang.String varianceCoveredTipText()

          Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

public void setVarianceCovered(double vc)

          Sets the amount of variance to account for when retaining principal components

Parameters:

vc - the proportion of total variance to account for

public double getVarianceCovered()

          Gets the proportion of total variance to account for when retaining principal components

Returns:

the proportion of variance to account for

public java.lang.String transformBackToOriginalTipText()

          Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

public void setTransformBackToOriginal(boolean b)

          Sets whether the data should be transformed back to the original space

Parameters:

b - true if the data should be transformed back to the original space

public boolean getTransformBackToOriginal()

          Gets whether the data is to be transformed back to the original space.

Returns:

true if the data is to be transformed back to the original space

public java.lang.String[] getOptions()

          Gets the current settings of PrincipalComponents

Returns:

an array of strings suitable for passing to setOptions()

public void buildEvaluator(Instances data) throws java.lang.Exception

          Initializes principal components and performs the analysis

Parameters:

data - the instances to analyse/transform

Throws:

java.lang.Exception - if analysis fails

Overrides:

buildEvaluator in class ASEvaluation

public Instances transformedHeader() throws java.lang.Exception

          Returns just the header for the transformed data (ie. an empty set of instances. This is so that AttributeSelection can determine the structure of the transformed data without actually having to get all the transformed data through getTransformedData().

Returns:

the header of the transformed data.

Throws:

java.lang.Exception - if the header of the transformed data can't be determined.

public Instances transformedData() throws java.lang.Exception

          Gets the transformed training data.

Returns:

the transformed training data

Throws:

java.lang.Exception - if transformed data can't be returned

public double evaluateAttribute(int att) throws java.lang.Exception

          Evaluates the merit of a transformed attribute. This is defined to be 1 minus the cumulative variance explained. Merit can't be meaningfully evaluated if the data is to be transformed back to the original space.

Parameters:

att - the attribute to be evaluated

Returns:

the merit of a transformed attribute

Throws:

java.lang.Exception - if attribute can't be evaluated

Overrides:

evaluateAttribute in class AttributeEvaluator

public java.lang.String toString()

          Returns a description of this attribute transformer

Returns:

a String describing this attribute transformer

Overrides:

toString in class java.lang.Object

public Instance convertInstance(Instance instance) throws java.lang.Exception

          Transform an instance in original (unormalized) format. Convert back to the original space if requested.

Parameters:

instance - an instance in the original (unormalized) format

Returns:

a transformed instance

Throws:

java.lang.Exception - if instance cant be transformed

public static void main(java.lang.String argv[])

          Main method for testing this class

Parameters:

argv - should contain the command line arguments to the evaluator/transformer (see AttributeSelection)

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