PrincipalComponents

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

All Implemented Interfaces:

java.io.Serializable, AttributeEvaluator, AttributeTransformer, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, 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: 15519 $

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

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`buildEvaluator(Instances data)` Initializes principal components and performs the analysis
`java.lang.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.
`double[][]`	`getCorrelationMatrix()` Return the correlation/covariance matrix
`double[]`	`getEigenValues()` Return the eigenvalues corresponding to the eigenvectors
`Instances`	`getFilteredInputFormat()` Return the header of the training data after all filtering - i.e missing values and nominal to binary.
`int`	`getMaximumAttributeNames()` Gets maximum number of attributes to include in transformed attribute names.
`java.lang.String[]`	`getOptions()` Gets the current settings of PrincipalComponents
`java.lang.String`	`getRevision()` Returns the revision string.
`boolean`	`getTransformBackToOriginal()` Gets whether the data is to be transformed back to the original space.
`double[][]`	`getUnsortedEigenVectors()` Return the unsorted eigenvectors
`double`	`getVarianceCovered()` Gets the proportion of total variance to account for when retaining principal components
`java.lang.String`	`globalInfo()` Returns a string describing this attribute transformer
`void`	`initializeAndComputeMatrix(Instances data)` Intializes the evaluator, filters the input data and computes the correlation/covariance matrix.
`java.util.Enumeration<Option>`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(java.lang.String[] argv)` Main method for testing this class
`static java.lang.String`	`matrixToString(double[][] matrix)` Return a matrix as a String
`java.lang.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(java.lang.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
`java.lang.String`	`toString()` Returns a description of this attribute transformer
`java.lang.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.
`java.lang.String`	`varianceCoveredTipText()` Returns the tip text for this property

Methods inherited from class weka.attributeSelection.ASEvaluation
clean, doNotCheckCapabilitiesTipText, forName, getDoNotCheckCapabilities, makeCopies, postExecution, postProcess, preExecution, run, runEvaluator, setDoNotCheckCapabilities

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.core.OptionHandler
makeCopy

- Constructor Detail
  - PrincipalComponents
```
public PrincipalComponents()
```
- Method Detail
  - globalInfo
```
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
  - listOptions
```
public java.util.Enumeration<Option> listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Overrides:
    
    listOptions in class ASEvaluation
    
    Returns:
    
    an enumeration of all the available options.
  - setOptions
```
public void setOptions(java.lang.String[] options)
                throws java.lang.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
    
    Overrides:
    
    setOptions in class ASEvaluation
    
    Parameters:
    
    options - the list of options as an array of strings
    
    Throws:
    
    java.lang.Exception - if an option is not supported
  - centerDataTipText
```
public java.lang.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 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
  - 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 java.lang.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 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
  - 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 java.lang.String[] getOptions()
```
    Gets the current settings of PrincipalComponents
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Overrides:
    
    getOptions in class ASEvaluation
    
    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 java.lang.Exception
```
    Initializes principal components and performs the analysis
    
    Specified by:
    
    buildEvaluator in class ASEvaluation
    
    Parameters:
    
    data - the instances to analyse/transform
    
    Throws:
    
    java.lang.Exception - if analysis fails
  - initializeAndComputeMatrix
```
public void initializeAndComputeMatrix(Instances data)
                                throws java.lang.Exception
```
    Intializes the evaluator, filters the input data and computes the correlation/covariance matrix.
    
    Parameters:
    
    data - the instances to analyse
    
    Throws:
    
    java.lang.Exception - if a problem occurs
  - transformedHeader
```
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 transformedData().
    
    Specified by:
    
    transformedHeader in interface AttributeTransformer
    
    Returns:
    
    the header of the transformed data.
    
    Throws:
    
    java.lang.Exception - if the header of the transformed data can't be determined.
  - getFilteredInputFormat
```
public Instances getFilteredInputFormat()
```
    Return the header of the training data after all filtering - i.e missing values and nominal to binary.
    
    Returns:
    
    the header of the training data after all filtering.
  - getCorrelationMatrix
```
public double[][] getCorrelationMatrix()
```
    Return the correlation/covariance matrix
    
    Returns:
    
    the correlation or covariance matrix
  - getUnsortedEigenVectors
```
public double[][] getUnsortedEigenVectors()
```
    Return the unsorted eigenvectors
    
    Returns:
    
    the unsorted eigenvectors
  - getEigenValues
```
public double[] getEigenValues()
```
    Return the eigenvalues corresponding to the eigenvectors
    
    Returns:
    
    the eigenvalues
  - transformedData
```
public Instances transformedData(Instances data)
                          throws java.lang.Exception
```
    Gets the transformed training data.
    
    Specified by:
    
    transformedData in interface AttributeTransformer
    
    Returns:
    
    the transformed training data
    
    Throws:
    
    java.lang.Exception - if transformed data can't be returned
  - evaluateAttribute
```
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.
    
    Specified by:
    
    evaluateAttribute in interface AttributeEvaluator
    
    Parameters:
    
    att - the attribute to be evaluated
    
    Returns:
    
    the merit of a transformed attribute
    
    Throws:
    
    java.lang.Exception - if attribute can't be evaluated
  - toString
```
public java.lang.String toString()
```
    Returns a description of this attribute transformer
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    a String describing this attribute transformer
  - matrixToString
```
public static java.lang.String matrixToString(double[][] matrix)
```
    Return a matrix as a String
    
    Parameters:
    
    matrix - that is decribed as a string
    
    Returns:
    
    a String describing a matrix
  - convertInstance
```
public Instance convertInstance(Instance instance)
                         throws java.lang.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:
    
    java.lang.Exception - if instance cant be transformed
  - getRevision
```
public java.lang.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(java.lang.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

Methods inherited from interface weka.core.OptionHandler

Constructor Detail

PrincipalComponents

Method Detail

globalInfo

listOptions

setOptions

centerDataTipText

setCenterData

getCenterData

varianceCoveredTipText

setVarianceCovered

getVarianceCovered

maximumAttributeNamesTipText

setMaximumAttributeNames

getMaximumAttributeNames

transformBackToOriginalTipText

setTransformBackToOriginal

getTransformBackToOriginal

getOptions

getCapabilities

buildEvaluator

initializeAndComputeMatrix

transformedHeader

getFilteredInputFormat

getCorrelationMatrix

getUnsortedEigenVectors

getEigenValues

transformedData

evaluateAttribute

toString

matrixToString

convertInstance

getRevision

main