Package weka.attributeSelection
Class CfsSubsetEval
- java.lang.Object
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- weka.attributeSelection.ASEvaluation
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- weka.attributeSelection.CfsSubsetEval
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- 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
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Constructor Summary
Constructors Constructor Description CfsSubsetEval()
Constructor
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method 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 attributesCapabilities
getCapabilities()
Returns the capabilities of this evaluator.boolean
getLocallyPredictive()
Return true if including locally predictive attributesboolean
getMissingSeparate()
Return true is missing is treated as a separate valuejava.lang.String[]
getOptions()
Gets the current settings of CfsSubsetEvaljava.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 evaluatorjava.util.Enumeration
listOptions()
Returns an enumeration describing the available options.java.lang.String
locallyPredictiveTipText()
Returns the tip text for this propertystatic void
main(java.lang.String[] args)
Main method for testing this class.java.lang.String
missingSeparateTipText()
Returns the tip text for this propertyint[]
postProcess(int[] attributeSet)
Calls locallyPredictive in order to include locally predictive attributes (if requested).void
setLocallyPredictive(boolean b)
Include locally predictive attributesvoid
setMissingSeparate(boolean b)
Treat missing as a separate valuevoid
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
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Method Detail
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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
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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 interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
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listOptions
public java.util.Enumeration listOptions()
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceOptionHandler
- Returns:
- an enumeration of all the available options.
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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 interfaceOptionHandler
- Parameters:
options
- the list of options as an array of strings- Throws:
java.lang.Exception
- if an option is not supported
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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
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setLocallyPredictive
public void setLocallyPredictive(boolean b)
Include locally predictive attributes- Parameters:
b
- true or false
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getLocallyPredictive
public boolean getLocallyPredictive()
Return true if including locally predictive attributes- Returns:
- true if locally predictive attributes are to be used
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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
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setMissingSeparate
public void setMissingSeparate(boolean b)
Treat missing as a separate value- Parameters:
b
- true or false
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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
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getOptions
public java.lang.String[] getOptions()
Gets the current settings of CfsSubsetEval- Specified by:
getOptions
in interfaceOptionHandler
- Returns:
- an array of strings suitable for passing to setOptions()
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getCapabilities
public Capabilities getCapabilities()
Returns the capabilities of this evaluator.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Overrides:
getCapabilities
in classASEvaluation
- Returns:
- the capabilities of this evaluator
- See Also:
Capabilities
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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 classASEvaluation
- Parameters:
data
- set of instances serving as training data- Throws:
java.lang.Exception
- if the evaluator has not been generated successfully
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evaluateSubset
public double evaluateSubset(java.util.BitSet subset) throws java.lang.Exception
evaluates a subset of attributes- Specified by:
evaluateSubset
in interfaceSubsetEvaluator
- 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
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toString
public java.lang.String toString()
returns a string describing CFS- Overrides:
toString
in classjava.lang.Object
- Returns:
- the description as a string
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postProcess
public int[] postProcess(int[] attributeSet) throws java.lang.Exception
Calls locallyPredictive in order to include locally predictive attributes (if requested).- Overrides:
postProcess
in classASEvaluation
- 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
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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 classASEvaluation
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classASEvaluation
- Returns:
- the revision
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main
public static void main(java.lang.String[] args)
Main method for testing this class.- Parameters:
args
- the options
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