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Class weka.attributeSelection.CfsSubsetEval 

java.lang.Object
   |
   +----weka.attributeSelection.ASEvaluation
           |
           +----weka.attributeSelection.SubsetEvaluator
                   |
                   +----weka.attributeSelection.CfsSubsetEval
public class CfsSubsetEval
extends SubsetEvaluator
implements OptionHandler
CFS attribute subset evaluator. For more information see:

Hall, M. A. (1998). Correlation-based Feature Subset Selection for Machine Learning. Thesis submitted in partial fulfilment of the requirements of the degree of Doctor of Philosophy at the University of Waikato.

Valid options are: -M
Treat missing values as a seperate value.

-L
Include locally predictive attributes.

Version:
$Revision: 1.6 $
Author:
Mark Hall (mhall@cs.waikato.ac.nz)

Constructor Index

o CfsSubsetEval()
Constructor

Method Index

o buildEvaluator(Instances)
Generates a attribute evaluator.
o evaluateSubset(BitSet)
evaluates a subset of attributes
o getLocallyPredictive()
Return true if including locally predictive attributes
o getMissingSeperate()
Return true is missing is treated as a seperate value
o getOptions()
Gets the current settings of CfsSubsetEval
o listOptions()
Returns an enumeration describing the available options
o main(String[])
Main method for testing this class.
o postProcess(int[])
Calls locallyPredictive in order to include locally predictive attributes (if requested).
o setLocallyPredictive(boolean)
Include locally predictive attributes
o setMissingSeperate(boolean)
Treat missing as a seperate value
o setOptions(String[])
Parses and sets a given list of options.
o toString()
returns a string describing CFS

Constructors

o CfsSubsetEval 
 public CfsSubsetEval()
Constructor

Methods

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

Returns:
an enumeration of all the available options
o setOptions 
 public void setOptions(String options[]) throws Exception
Parses and sets a given list of options.

Valid options are: -M
Treat missing values as a seperate value.

-L
Include locally predictive attributes.

Parameters:
options - the list of options as an array of strings
Throws: Exception
if an option is not supported
o setLocallyPredictive 
 public void setLocallyPredictive(boolean b)
Include locally predictive attributes

Parameters:
b - true or false
o getLocallyPredictive 
 public boolean getLocallyPredictive()
Return true if including locally predictive attributes

Returns:
true if locally predictive attributes are to be used
o setMissingSeperate 
 public void setMissingSeperate(boolean b)
Treat missing as a seperate value

Parameters:
b - true or false
o getMissingSeperate 
 public boolean getMissingSeperate()
Return true is missing is treated as a seperate value

Returns:
true if missing is to be treated as a seperate value
o getOptions 
 public String[] getOptions()
Gets the current settings of CfsSubsetEval

Returns:
an array of strings suitable for passing to setOptions()
o buildEvaluator 
 public void buildEvaluator(Instances data) throws 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.

Parameters:
data - set of instances serving as training data
Throws: Exception
if the evaluator has not been generated successfully
Overrides:
buildEvaluator in class ASEvaluation
o evaluateSubset 
 public double evaluateSubset(BitSet subset) throws Exception
evaluates a subset of attributes

Parameters:
subset - a bitset representing the attribute subset to be evaluated
Throws: Exception
if the subset could not be evaluated
Overrides:
evaluateSubset in class SubsetEvaluator
o toString 
 public String toString()
returns a string describing CFS

Returns:
the description as a string
Overrides:
toString in class Object
o postProcess 
 public int[] postProcess(int attributeSet[]) throws Exception
Calls locallyPredictive in order to include locally predictive attributes (if requested).

Parameters:
attributeSet - the set of attributes found by the search
Returns:
a possibly ranked list of postprocessed attributes
Throws: Exception
if postprocessing fails for some reason
Overrides:
postProcess in class ASEvaluation
o main 
 public static void main(String args[])
Main method for testing this class.

Parameters:
args - the options 
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