Uses of Class
weka.attributeSelection.ASEvaluation

Packages that use ASEvaluation
weka.attributeSelection   
weka.classifiers.meta   
weka.filters.supervised.attribute   
 

Uses of ASEvaluation in weka.attributeSelection
 

Subclasses of ASEvaluation in weka.attributeSelection
 class AttributeSetEvaluator
          Abstract attribute set evaluator.
 class CfsSubsetEval
          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.
 class GainRatioAttributeEval
          GainRatioAttributeEval :

Evaluates the worth of an attribute by measuring the gain ratio with respect to the class.

GainR(Class, Attribute) = (H(Class) - H(Class | Attribute)) / H(Attribute).

Valid options are:

 class HoldOutSubsetEvaluator
          Abstract attribute subset evaluator capable of evaluating subsets with respect to a data set that is distinct from that used to initialize/ train the subset evaluator.
 class InfoGainAttributeEval
          InfoGainAttributeEval :

Evaluates the worth of an attribute by measuring the information gain with respect to the class.

InfoGain(Class,Attribute) = H(Class) - H(Class | Attribute).

Valid options are:

 class OneRAttributeEval
          OneRAttributeEval :

Evaluates the worth of an attribute by using the OneR classifier.

Valid options are:

 class PrincipalComponents
          Performs a principal components analysis and transformation of the data.
 class ReliefFAttributeEval
          ReliefFAttributeEval :

Evaluates the worth of an attribute by repeatedly sampling an instance and considering the value of the given attribute for the nearest instance of the same and different class.
 class SymmetricalUncertAttributeEval
          SymmetricalUncertAttributeEval :

Evaluates the worth of an attribute by measuring the symmetrical uncertainty with respect to the class.
 class UnsupervisedAttributeEvaluator
          Abstract unsupervised attribute evaluator.
 class UnsupervisedSubsetEvaluator
          Abstract unsupervised attribute subset evaluator.
 class WrapperSubsetEval
          WrapperSubsetEval:

Evaluates attribute sets by using a learning scheme.
 

Methods in weka.attributeSelection that return ASEvaluation
static ASEvaluation ASEvaluation.forName(String evaluatorName, String[] options)
          Creates a new instance of an attribute/subset evaluator given it's class name and (optional) arguments to pass to it's setOptions method.
 ASEvaluation CheckAttributeSelection.getEvaluator()
          Get the current evaluator
static ASEvaluation[] ASEvaluation.makeCopies(ASEvaluation model, int num)
          Creates copies of the current evaluator.
 

Methods in weka.attributeSelection with parameters of type ASEvaluation
static ASEvaluation[] ASEvaluation.makeCopies(ASEvaluation model, int num)
          Creates copies of the current evaluator.
static void ASEvaluation.runEvaluator(ASEvaluation evaluator, String[] options)
          runs the evaluator with the given commandline options
 int[] BestFirst.search(ASEvaluation ASEval, Instances data)
          Searches the attribute subset space by best first search
abstract  int[] ASSearch.search(ASEvaluation ASEvaluator, Instances data)
          Searches the attribute subset/ranking space.
 int[] GreedyStepwise.search(ASEvaluation ASEval, Instances data)
          Searches the attribute subset space by forward selection.
 int[] Ranker.search(ASEvaluation ASEval, Instances data)
          Kind of a dummy search algorithm.
static String AttributeSelection.SelectAttributes(ASEvaluation ASEvaluator, String[] options)
          Perform attribute selection with a particular evaluator and a set of options specifying search method and input file etc.
static String AttributeSelection.SelectAttributes(ASEvaluation ASEvaluator, String[] options, Instances train)
          Perform attribute selection with a particular evaluator and a set of options specifying search method and options for the search method and evaluator.
 void AttributeSelection.setEvaluator(ASEvaluation evaluator)
          set the attribute/subset evaluator
 void CheckAttributeSelection.setEvaluator(ASEvaluation value)
          Set the evaluator to test.
 

Uses of ASEvaluation in weka.classifiers.meta
 

Methods in weka.classifiers.meta that return ASEvaluation
 ASEvaluation AttributeSelectedClassifier.getEvaluator()
          Gets the attribute evaluator used
 

Methods in weka.classifiers.meta with parameters of type ASEvaluation
 void AttributeSelectedClassifier.setEvaluator(ASEvaluation evaluator)
          Sets the attribute evaluator
 

Uses of ASEvaluation in weka.filters.supervised.attribute
 

Methods in weka.filters.supervised.attribute that return ASEvaluation
 ASEvaluation AttributeSelection.getEvaluator()
          Get the name of the attribute/subset evaluator
 

Methods in weka.filters.supervised.attribute with parameters of type ASEvaluation
 void AttributeSelection.setEvaluator(ASEvaluation evaluator)
          set attribute/subset evaluator
 



Copyright © 2012 University of Waikato, Hamilton, NZ. All Rights Reserved.