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	ChiSquaredAttributeEval ChiSquaredAttributeEval : Evaluates the worth of an attribute by computing the value of the chi-squared statistic with respect to the class. Valid options are:
class	ClassifierSubsetEval Classifier subset evaluator: Evaluates attribute subsets on training data or a seperate hold out testing set.
class	ConsistencySubsetEval ConsistencySubsetEval : Evaluates the worth of a subset of attributes by the level of consistency in the class values when the training instances are projected onto the subset of attributes.
class	CostSensitiveASEvaluation Abstract base class for cost-sensitive subset and attribute evaluators.
class	CostSensitiveAttributeEval A meta subset evaluator that makes its base subset evaluator cost-sensitive.
class	CostSensitiveSubsetEval A meta subset evaluator that makes its base subset evaluator cost-sensitive.
class	FilteredAttributeEval Class for running an arbitrary attribute evaluator on data that has been passed through an arbitrary filter (note: filters that alter the order or number of attributes are not allowed).
class	FilteredSubsetEval Class for running an arbitrary subset evaluator on data that has been passed through an arbitrary filter (note: filters that alter the order or number of attributes are not allowed).
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	LatentSemanticAnalysis Performs latent semantic analysis and transformation of the data.
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	SVMAttributeEval SVMAttributeEval : Evaluates the worth of an attribute by using an SVM classifier.
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	FilteredAttributeEval.getAttributeEvaluator() Get the attribute evaluator to use
ASEvaluation	RankSearch.getAttributeEvaluator() Get the attribute evaluator used to generate the ranking.
ASEvaluation	RaceSearch.getAttributeEvaluator() Get the attribute evaluator used to generate the ranking.
ASEvaluation	CheckAttributeSelection.getEvaluator() Get the current evaluator
ASEvaluation	CostSensitiveASEvaluation.getEvaluator() Get the evaluator used as the base evaluator.
ASEvaluation	FilteredSubsetEval.getSubsetEvaluator() Get the subset evaluator to use
ASEvaluation	SubsetSizeForwardSelection.getSubsetSizeEvaluator() Get the subset evaluator used for subset size determination.
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.
int[]	BestFirst.search(ASEvaluation ASEval, Instances data) Searches the attribute subset space by best first search
int[]	ExhaustiveSearch.search(ASEvaluation ASEval, Instances data) Searches the attribute subset space using an exhaustive search.
int[]	RandomSearch.search(ASEvaluation ASEval, Instances data) Searches the attribute subset space randomly.
int[]	RankSearch.search(ASEvaluation ASEval, Instances data) Ranks attributes using the specified attribute evaluator and then searches the ranking using the supplied subset evaluator.
int[]	SubsetSizeForwardSelection.search(ASEvaluation ASEval, Instances data) Searches the attribute subset space by subset size forward selection
abstract int[]	ASSearch.search(ASEvaluation ASEvaluator, Instances data) Searches the attribute subset/ranking space.
int[]	ScatterSearchV1.search(ASEvaluation ASEval, Instances data) Searches the attribute subset space using Scatter Search.
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.
int[]	GeneticSearch.search(ASEvaluation ASEval, Instances data) Searches the attribute subset space using a genetic algorithm.
int[]	RaceSearch.search(ASEvaluation ASEval, Instances data) Searches the attribute subset space by racing cross validation errors of competing subsets
int[]	LinearForwardSelection.search(ASEvaluation ASEval, Instances data) Searches the attribute subset space by linear forward selection
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	FilteredAttributeEval.setAttributeEvaluator(ASEvaluation newEvaluator) Set the attribute evaluator to use
void	RankSearch.setAttributeEvaluator(ASEvaluation newEvaluator) Set the attribute evaluator to use for generating the ranking.
void	RaceSearch.setAttributeEvaluator(ASEvaluation newEvaluator) Set the attribute evaluator to use for generating the ranking.
void	AttributeSelection.setEvaluator(ASEvaluation evaluator) set the attribute/subset evaluator
void	CostSensitiveAttributeEval.setEvaluator(ASEvaluation newEvaluator) Set the base evaluator.
void	CostSensitiveSubsetEval.setEvaluator(ASEvaluation newEvaluator) Set the base evaluator.
void	CheckAttributeSelection.setEvaluator(ASEvaluation value) Set the evaluator to test.
void	CostSensitiveASEvaluation.setEvaluator(ASEvaluation newEvaluator) Set the base evaluator.
void	FilteredSubsetEval.setSubsetEvaluator(ASEvaluation newEvaluator) Set the subset evaluator to use
void	SubsetSizeForwardSelection.setSubsetSizeEvaluator(ASEvaluation eval) Set the subset evaluator to use for subset size determination.

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