# Package weka.attributeSelection

package weka.attributeSelection

Class
Description
ASEvaluation
Abstract attribute selection evaluation class
ASSearch
Abstract attribute selection search class.
AttributeEvaluator
Interface for classes that evaluate attributes individually.
AttributeSelection
Attribute selection class.
AttributeSetEvaluator
Abstract attribute set evaluator.
AttributeTransformer
Abstract attribute transformer.
BestFirst
BestFirst:
Searches the space of attribute subsets by greedy hillclimbing augmented with a backtracking facility.
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.
CheckAttributeSelection
Class for examining the capabilities and finding problems with attribute selection schemes.
ChiSquaredAttributeEval
ChiSquaredAttributeEval :
Evaluates the worth of an attribute by computing the value of the chi-squared statistic with respect to the class.
ClassifierSubsetEval
Classifier subset evaluator:
Evaluates attribute subsets on training data or a seperate hold out testing set.
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.
CostSensitiveASEvaluation
Abstract base class for cost-sensitive subset and attribute evaluators.
CostSensitiveAttributeEval
A meta subset evaluator that makes its base subset evaluator cost-sensitive.
CostSensitiveSubsetEval
A meta subset evaluator that makes its base subset evaluator cost-sensitive.
ErrorBasedMeritEvaluator
Interface for evaluators that calculate the "merit" of attributes/subsets as the error of a learning scheme
ExhaustiveSearch
ExhaustiveSearch :
Performs an exhaustive search through the space of attribute subsets starting from the empty set of attrubutes.
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).
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).
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).
GeneticSearch
GeneticSearch:
Performs a search using the simple genetic algorithm described in Goldberg (1989).
For more information see:
David E.
GreedyStepwise
GreedyStepwise :
Performs a greedy forward or backward search through the space of attribute subsets.
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.
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).
LatentSemanticAnalysis
Performs latent semantic analysis and transformation of the data.
LFSMethods
LinearForwardSelection
LinearForwardSelection:
Extension of BestFirst.
OneRAttributeEval
OneRAttributeEval :
Evaluates the worth of an attribute by using the OneR classifier.
PrincipalComponents
Performs a principal components analysis and transformation of the data.
RaceSearch
Races the cross validation error of competing attribute subsets.
RandomSearch
RandomSearch :
Performs a Random search in the space of attribute subsets.
RankedOutputSearch
Interface for search methods capable of producing a ranked list of attributes.
Ranker
Ranker :
Ranks attributes by their individual evaluations.
RankSearch
RankSearch :
Uses an attribute/subset evaluator to rank all attributes.
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.
ScatterSearchV1
Class for performing the Sequential Scatter Search.
StartSetHandler
Interface for search methods capable of doing something sensible given a starting set of attributes.
SubsetEvaluator
Interface for attribute subset evaluators.
SubsetSizeForwardSelection
SubsetSizeForwardSelection:
Extension of LinearForwardSelection.
SVMAttributeEval
SVMAttributeEval :
Evaluates the worth of an attribute by using an SVM classifier.
SymmetricalUncertAttributeEval
SymmetricalUncertAttributeEval :
Evaluates the worth of an attribute by measuring the symmetrical uncertainty with respect to the class.
UnsupervisedAttributeEvaluator
Abstract unsupervised attribute evaluator.
UnsupervisedSubsetEvaluator
Abstract unsupervised attribute subset evaluator.
WrapperSubsetEval
WrapperSubsetEval:
Evaluates attribute sets by using a learning scheme.