PrincipalComponents (weka-dev 3.7.6-SNAPSHOT API)

java.lang.Object
- weka.attributeSelection.ASEvaluation
- - weka.attributeSelection.UnsupervisedAttributeEvaluator
  - - weka.attributeSelection.PrincipalComponents

All Implemented Interfaces:

Serializable, AttributeEvaluator, AttributeTransformer, CapabilitiesHandler, OptionHandler, RevisionHandler
```
public class PrincipalComponents
extends UnsupervisedAttributeEvaluator
implements AttributeTransformer, OptionHandler
```
Performs a principal components analysis and transformation of the data. Use in conjunction with a Ranker search. Dimensionality reduction is accomplished by choosing enough eigenvectors to account for some percentage of the variance in the original data---default 0.95 (95%). Attribute noise can be filtered by transforming to the PC space, eliminating some of the worst eigenvectors, and then transforming back to the original space.
Valid options are:
```
 -C
  Center (rather than standardize) the
  data and compute PCA using the covariance (rather
   than the correlation) matrix.
```
```
 -R
  Retain enough PC attributes to account 
  for this proportion of variance in the original data.
  (default = 0.95)
```
```
 -O
  Transform through the PC space and 
  back to the original space.
```
```
 -A
  Maximum number of attributes to include in 
  transformed attribute names. (-1 = include all)
```
Version:

$Revision: 8034 $

Author:

Mark Hall (mhall@cs.waikato.ac.nz), Gabi Schmidberger (gabi@cs.waikato.ac.nz)

See Also:
Serialized Form

Constructor Summary

Constructors
Constructor and Description

PrincipalComponents()

Constructors
Constructor and Description
`PrincipalComponents()`

Method Summary

Methods
Modifier and Type	Method and Description
`void`	`buildEvaluator(Instances data)` Initializes principal components and performs the analysis
`String`	`centerDataTipText()` Returns the tip text for this property
`Instance`	`convertInstance(Instance instance)` Transform an instance in original (unormalized) format.
`double`	`evaluateAttribute(int att)` Evaluates the merit of a transformed attribute.
`Capabilities`	`getCapabilities()` Returns the capabilities of this evaluator.
`boolean`	`getCenterData()` Get whether to center (rather than standardize) the data.
`int`	`getMaximumAttributeNames()` Gets maximum number of attributes to include in transformed attribute names.
`String[]`	`getOptions()` Gets the current settings of PrincipalComponents
`String`	`getRevision()` Returns the revision string.
`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.
`static void`	`main(String[] argv)` Main method for testing this class
`String`	`maximumAttributeNamesTipText()` Returns the tip text for this property
`void`	`setCenterData(boolean center)` Set whether to center (rather than standardize) the data.
`void`	`setMaximumAttributeNames(int m)` Sets maximum number of attributes to include in transformed attribute names.
`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(Instances data)` Gets the transformed training data.
`Instances`	`transformedHeader()` Returns just the header for the transformed data (ie.
`String`	`varianceCoveredTipText()` Returns the tip text for this property

Methods inherited from class weka.attributeSelection.ASEvaluation
forName, makeCopies, postProcess, runEvaluator

Methods inherited from class java.lang.Object
equals, 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.
    
    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:
```
 -C
  Center (rather than standardize) the
  data and compute PCA using the covariance (rather
   than the correlation) matrix.
```
```
 -R
  Retain enough PC attributes to account 
  for this proportion of variance in the original data.
  (default = 0.95)
```
```
 -O
  Transform through the PC space and 
  back to the original space.
```
```
 -A
  Maximum number of attributes to include in 
  transformed attribute names. (-1 = include all)
```
    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
  - centerDataTipText
```
public String centerDataTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setCenterData
```
public void setCenterData(boolean center)
```
    Set whether to center (rather than standardize) the data. If set to true then PCA is computed from the covariance rather than correlation matrix.
    
    Parameters:
    center - true if the data is to be centered rather than standardized
  - getCenterData
```
public boolean getCenterData()
```
    Get whether to center (rather than standardize) the data. If true then PCA is computed from the covariance rather than correlation matrix.
    
    Returns:
    true if the data is to be centered rather than standardized.
  - 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
  - maximumAttributeNamesTipText
```
public String maximumAttributeNamesTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setMaximumAttributeNames
```
public void setMaximumAttributeNames(int m)
```
    Sets maximum number of attributes to include in transformed attribute names.
    
    Parameters:
    m - the maximum number of attributes
  - getMaximumAttributeNames
```
public int getMaximumAttributeNames()
```
    Gets maximum number of attributes to include in transformed attribute names.
    
    Returns:
    the maximum number of attributes
  - 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()
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns the capabilities of this evaluator.
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class ASEvaluation
    
    Returns:
    the capabilities of this evaluator
    See Also:
    Capabilities
  - 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 transformedData().
    
    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(Instances data)
                          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 interface 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
  - getRevision
```
public String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class ASEvaluation
    
    Returns:
    the revision
  - 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)

Class PrincipalComponents

Constructor Summary

Method Summary

Methods inherited from class weka.attributeSelection.ASEvaluation

Methods inherited from class java.lang.Object

Constructor Detail

PrincipalComponents

Method Detail

globalInfo

listOptions

setOptions

centerDataTipText

setCenterData

getCenterData

varianceCoveredTipText

setVarianceCovered

getVarianceCovered

maximumAttributeNamesTipText

setMaximumAttributeNames

getMaximumAttributeNames

transformBackToOriginalTipText

setTransformBackToOriginal

getTransformBackToOriginal

getOptions

getCapabilities

buildEvaluator

transformedHeader

transformedData

evaluateAttribute

toString

convertInstance

getRevision

main