weka.attributeSelection
Class PrincipalComponents

java.lang.Object
  |
  +--weka.attributeSelection.ASEvaluation
        |
        +--weka.attributeSelection.AttributeEvaluator
              |
              +--weka.attributeSelection.PrincipalComponents
All Implemented Interfaces:
AttributeTransformer, OptionHandler, Serializable

public class PrincipalComponents
extends AttributeEvaluator
implements AttributeTransformer, OptionHandler

Class for performing principal components analysis/transformation.

Version:
$Revision: 1.16 $
Author:
Mark Hall (mhall@cs.waikato.ac.nz)
See Also:
Serialized Form

Constructor Summary
PrincipalComponents()
           
 
Method Summary
 void buildEvaluator(Instances data)
          Initializes principal components and performs the analysis
 Instance convertInstance(Instance instance)
          Transform an instance in original (unormalized) format.
 double evaluateAttribute(int att)
          Evaluates the merit of a transformed attribute.
 boolean getNormalize()
          Gets whether or not input data is to be normalized
 String[] getOptions()
          Gets the current settings of PrincipalComponents
 boolean getTransformBackToOriginal()
          Gets whether the data is to be transformed back to the original space.
 double getVarianceCovered()
          Gets the proportion of total variance to account for when retaining principal components
 String globalInfo()
          Returns a string describing this attribute transformer
 Enumeration listOptions()
          Returns an enumeration describing the available options -N Don't normalize the input data.
static void main(String[] argv)
          Main method for testing this class
 String normalizeTipText()
          Returns the tip text for this property
 void setNormalize(boolean n)
          Set whether input data will be normalized.
 void setOptions(String[] options)
          Parses a given list of options.
 void setTransformBackToOriginal(boolean b)
          Sets whether the data should be transformed back to the original space
 void setVarianceCovered(double vc)
          Sets the amount of variance to account for when retaining principal components
 String toString()
          Returns a description of this attribute transformer
 String transformBackToOriginalTipText()
          Returns the tip text for this property
 Instances transformedData()
          Gets the transformed training data.
 Instances transformedHeader()
          Returns just the header for the transformed data (ie. an empty set of instances.
 String varianceCoveredTipText()
          Returns the tip text for this property
 
Methods inherited from class weka.attributeSelection.ASEvaluation
forName, makeCopies, postProcess
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

PrincipalComponents

public PrincipalComponents()
Method Detail

globalInfo

public String globalInfo()
Returns a string describing this attribute transformer

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

listOptions

public Enumeration listOptions()
Returns an enumeration describing the available options

-N Don't normalize the input data.

Specified by:
listOptions in interface OptionHandler
Returns:
an enumeration of all the available options

setOptions

public void setOptions(String[] options)
                throws Exception
Parses a given list of options. Valid options are:

-N Don't normalize the input data.

Specified by:
setOptions in interface OptionHandler
Parameters:
options - the list of options as an array of strings
Throws:
Exception - if an option is not supported

normalizeTipText

public String normalizeTipText()
Returns the tip text for this property

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

setNormalize

public void setNormalize(boolean n)
Set whether input data will be normalized.

Parameters:
n - true if input data is to be normalized

getNormalize

public boolean getNormalize()
Gets whether or not input data is to be normalized

Returns:
true if input data is to be normalized

varianceCoveredTipText

public String varianceCoveredTipText()
Returns the tip text for this property

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

setVarianceCovered

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

getVarianceCovered

public double getVarianceCovered()
Gets the proportion of total variance to account for when retaining principal components

Returns:
the proportion of variance to account for

transformBackToOriginalTipText

public String transformBackToOriginalTipText()
Returns the tip text for this property

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

setTransformBackToOriginal

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

getTransformBackToOriginal

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

getOptions

public String[] getOptions()
Gets the current settings of PrincipalComponents

Specified by:
getOptions in interface OptionHandler
Returns:
an array of strings suitable for passing to setOptions()

buildEvaluator

public void buildEvaluator(Instances data)
                    throws Exception
Initializes principal components and performs the analysis

Specified by:
buildEvaluator in class ASEvaluation
Parameters:
data - the instances to analyse/transform
Throws:
Exception - if analysis fails

transformedHeader

public Instances transformedHeader()
                            throws 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().

Specified by:
transformedHeader in interface AttributeTransformer
Returns:
the header of the transformed data.
Throws:
Exception - if the header of the transformed data can't be determined.

transformedData

public Instances transformedData()
                          throws Exception
Gets the transformed training data.

Specified by:
transformedData in interface AttributeTransformer
Returns:
the transformed training data
Throws:
Exception - if transformed data can't be returned

evaluateAttribute

public double evaluateAttribute(int att)
                         throws 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.

Specified by:
evaluateAttribute in class AttributeEvaluator
Parameters:
att - the attribute to be evaluated
Returns:
the merit of a transformed attribute
Throws:
Exception - if attribute can't be evaluated

toString

public String toString()
Returns a description of this attribute transformer

Overrides:
toString in class Object
Returns:
a String describing this attribute transformer

convertInstance

public Instance convertInstance(Instance instance)
                         throws Exception
Transform an instance in original (unormalized) format. Convert back to the original space if requested.

Specified by:
convertInstance in interface AttributeTransformer
Parameters:
instance - an instance in the original (unormalized) format
Returns:
a transformed instance
Throws:
Exception - if instance cant be transformed

main

public static void main(String[] argv)
Main method for testing this class

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