Uses of Interface
weka.attributeSelection.SubsetEvaluator

Packages that use SubsetEvaluator

weka.attributeSelection

Uses of SubsetEvaluator in weka.attributeSelection

Classes in weka.attributeSelection that implement SubsetEvaluator

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	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	CostSensitiveSubsetEval A meta subset evaluator that makes its base subset evaluator cost-sensitive.
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	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	UnsupervisedSubsetEvaluator Abstract unsupervised attribute subset evaluator.
class	WrapperSubsetEval WrapperSubsetEval: Evaluates attribute sets by using a learning scheme.

Methods in weka.attributeSelection with parameters of type SubsetEvaluator

BitSet	LFSMethods.floatingForwardSearch(int cacheSize, BitSet startGroup, int[] ranking, int k, boolean incrementK, int maxStale, Instances data, SubsetEvaluator evaluator, boolean verbose) Performs linear floating forward selection ( the stopping criteria cannot be changed to a specific size value )
BitSet	LFSMethods.forwardSearch(int cacheSize, BitSet startGroup, int[] ranking, int k, boolean incrementK, int maxStale, int forceResultSize, Instances data, SubsetEvaluator evaluator, boolean verbose) Performs linear forward selection
int[]	LFSMethods.rankAttributes(Instances data, SubsetEvaluator evaluator, boolean verbose)