CfsSubsetEval

java.lang.Object
- weka.attributeSelection.ASEvaluation
- - weka.attributeSelection.CfsSubsetEval

All Implemented Interfaces:

java.io.Serializable, SubsetEvaluator, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler
```
public class CfsSubsetEval
extends ASEvaluation
implements SubsetEvaluator, OptionHandler, TechnicalInformationHandler
```
CfsSubsetEval :

Evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them.

Subsets of features that are highly correlated with the class while having low intercorrelation are preferred.

For more information see:

M. A. Hall (1998). Correlation-based Feature Subset Selection for Machine Learning. Hamilton, New Zealand.
BibTeX:
```
 @phdthesis{Hall1998,
    address = {Hamilton, New Zealand},
    author = {M. A. Hall},
    school = {University of Waikato},
    title = {Correlation-based Feature Subset Selection for Machine Learning},
    year = {1998}
 }
 
```
Valid options are:
```
 -M
  Treat missing values as a separate value.
 
```
```
 -L
  Don't include locally predictive attributes.
 
```
Version:

$Revision: 11851 $

Author:

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

See Also:

Discretize, Serialized Form

Constructor Summary

Constructors
Constructor and Description

CfsSubsetEval()
Constructor

Constructors
Constructor and Description
`CfsSubsetEval()` Constructor

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`buildEvaluator(Instances data)` Generates a attribute evaluator.
`void`	`clean()` Tells the evaluator that the attribute selection process is complete.
`double`	`evaluateSubset(java.util.BitSet subset)` evaluates a subset of attributes
`Capabilities`	`getCapabilities()` Returns the capabilities of this evaluator.
`boolean`	`getLocallyPredictive()` Return true if including locally predictive attributes
`boolean`	`getMissingSeparate()` Return true is missing is treated as a separate value
`java.lang.String[]`	`getOptions()` Gets the current settings of CfsSubsetEval
`java.lang.String`	`getRevision()` Returns the revision string.
`TechnicalInformation`	`getTechnicalInformation()` Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
`java.lang.String`	`globalInfo()` Returns a string describing this attribute evaluator
`java.util.Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`java.lang.String`	`locallyPredictiveTipText()` Returns the tip text for this property
`static void`	`main(java.lang.String[] args)` Main method for testing this class.
`java.lang.String`	`missingSeparateTipText()` Returns the tip text for this property
`int[]`	`postProcess(int[] attributeSet)` Calls locallyPredictive in order to include locally predictive attributes (if requested).
`void`	`setLocallyPredictive(boolean b)` Include locally predictive attributes
`void`	`setMissingSeparate(boolean b)` Treat missing as a separate value
`void`	`setOptions(java.lang.String[] options)` Parses and sets a given list of options.
`java.lang.String`	`toString()` returns a string describing CFS

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

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

- Constructor Detail
  - CfsSubsetEval
```
public CfsSubsetEval()
```
    Constructor
- Method Detail
  - globalInfo
```
public java.lang.String globalInfo()
```
    Returns a string describing this attribute evaluator
    
    Returns:
    
    a description of the evaluator suitable for displaying in the explorer/experimenter gui
  - getTechnicalInformation
```
public TechnicalInformation getTechnicalInformation()
```
    Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
    
    Specified by:
    
    getTechnicalInformation in interface TechnicalInformationHandler
    
    Returns:
    
    the technical information about this class
  - listOptions
```
public java.util.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(java.lang.String[] options)
                throws java.lang.Exception
```
    Parses and sets a given list of options.
    Valid options are:
```
 -M
  Treat missing values as a separate value.
 
```
```
 -L
  Don't include locally predictive attributes.
 
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Parameters:
    
    options - the list of options as an array of strings
    
    Throws:
    
    java.lang.Exception - if an option is not supported
  - locallyPredictiveTipText
```
public java.lang.String locallyPredictiveTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setLocallyPredictive
```
public void setLocallyPredictive(boolean b)
```
    Include locally predictive attributes
    
    Parameters:
    
    b - true or false
  - getLocallyPredictive
```
public boolean getLocallyPredictive()
```
    Return true if including locally predictive attributes
    
    Returns:
    
    true if locally predictive attributes are to be used
  - missingSeparateTipText
```
public java.lang.String missingSeparateTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setMissingSeparate
```
public void setMissingSeparate(boolean b)
```
    Treat missing as a separate value
    
    Parameters:
    
    b - true or false
  - getMissingSeparate
```
public boolean getMissingSeparate()
```
    Return true is missing is treated as a separate value
    
    Returns:
    
    true if missing is to be treated as a separate value
  - getOptions
```
public java.lang.String[] getOptions()
```
    Gets the current settings of CfsSubsetEval
    
    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 java.lang.Exception
```
    Generates a attribute evaluator. Has to initialize all fields of the evaluator that are not being set via options. CFS also discretises attributes (if necessary) and initializes the correlation matrix.
    
    Specified by:
    
    buildEvaluator in class ASEvaluation
    
    Parameters:
    
    data - set of instances serving as training data
    
    Throws:
    
    java.lang.Exception - if the evaluator has not been generated successfully
  - evaluateSubset
```
public double evaluateSubset(java.util.BitSet subset)
                      throws java.lang.Exception
```
    evaluates a subset of attributes
    
    Specified by:
    
    evaluateSubset in interface SubsetEvaluator
    
    Parameters:
    
    subset - a bitset representing the attribute subset to be evaluated
    
    Returns:
    
    the merit
    
    Throws:
    
    java.lang.Exception - if the subset could not be evaluated
  - toString
```
public java.lang.String toString()
```
    returns a string describing CFS
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    the description as a string
  - postProcess
```
public int[] postProcess(int[] attributeSet)
                  throws java.lang.Exception
```
    Calls locallyPredictive in order to include locally predictive attributes (if requested).
    
    Overrides:
    
    postProcess in class ASEvaluation
    
    Parameters:
    
    attributeSet - the set of attributes found by the search
    
    Returns:
    
    a possibly ranked list of postprocessed attributes
    
    Throws:
    
    java.lang.Exception - if postprocessing fails for some reason
  - clean
```
public void clean()
```
    Description copied from class: ASEvaluation
    
    Tells the evaluator that the attribute selection process is complete. It can then clean up data structures, references to training data as necessary in order to save memory
    
    Overrides:
    
    clean in class ASEvaluation
  - 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[] args)
```
    Main method for testing this class.
    
    Parameters:
    
    args - the options

Class CfsSubsetEval

Constructor Summary

Method Summary

Methods inherited from class weka.attributeSelection.ASEvaluation

Methods inherited from class java.lang.Object

Constructor Detail

CfsSubsetEval

Method Detail

globalInfo

getTechnicalInformation

listOptions

setOptions

locallyPredictiveTipText

setLocallyPredictive

getLocallyPredictive

missingSeparateTipText

setMissingSeparate

getMissingSeparate

getOptions

getCapabilities

buildEvaluator

evaluateSubset

toString

postProcess

clean

getRevision

main