Index

A C D E G I L M N P R S T V W

A

attributeEvaluatorTipText() - Method in class weka.attributeSelection.RankSearch: Returns the tip text for this property

C

crossoverProbTipText() - Method in class weka.attributeSelection.GeneticSearch: Returns the tip text for this property

D

debuggingOutputTipText() - Method in class weka.attributeSelection.RankSearch: Returns the tip text for this property

E

excludeNonImprovingAttributesTipText() - Method in class weka.attributeSelection.RankSearch: Returns the tip text for this property
ExhaustiveSearch - Class in weka.attributeSelection: ExhaustiveSearch :

Performs an exhaustive search through the space of attribute subsets starting from the empty set of attrubutes.
ExhaustiveSearch() - Constructor for class weka.attributeSelection.ExhaustiveSearch: Constructor

G

GeneticSearch - Class in weka.attributeSelection: GeneticSearch:

Performs a search using the simple genetic algorithm described in Goldberg (1989).

For more information see:

David E.
GeneticSearch() - Constructor for class weka.attributeSelection.GeneticSearch: Constructor.
getAttributeEvaluator() - Method in class weka.attributeSelection.RankSearch: Get the attribute evaluator used to generate the ranking.
getCrossoverProb() - Method in class weka.attributeSelection.GeneticSearch: get the probability of crossover
getDebuggingOutput() - Method in class weka.attributeSelection.RankSearch: Get whether to output debugging info to the console
getExcludeNonImprovingAttributes() - Method in class weka.attributeSelection.RankSearch: Get whether or not to add prior non-improving attributes when considering more attributes from the ranked list
getImprovementThreshold() - Method in class weka.attributeSelection.RankSearch: Get merit improvement threshold
getMaxGenerations() - Method in class weka.attributeSelection.GeneticSearch: get the number of generations
getMutationProb() - Method in class weka.attributeSelection.GeneticSearch: get the probability of mutation
getNonImprovingAdditions() - Method in class weka.attributeSelection.RankSearch: Get the number of consecutive non-improving additions to tolerate before terminating the search
getOptions() - Method in class weka.attributeSelection.ExhaustiveSearch: Gets the current settings of RandomSearch.
getOptions() - Method in class weka.attributeSelection.GeneticSearch: Gets the current settings of ReliefFAttributeEval.
getOptions() - Method in class weka.attributeSelection.RandomSearch: Gets the current settings of RandomSearch.
getOptions() - Method in class weka.attributeSelection.RankSearch: Gets the current settings of WrapperSubsetEval.
getPopulationSize() - Method in class weka.attributeSelection.GeneticSearch: get the size of the population
getReportFrequency() - Method in class weka.attributeSelection.GeneticSearch: get how often repports are generated
getRevision() - Method in class weka.attributeSelection.ExhaustiveSearch: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.GeneticSearch: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.RandomSearch: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.RankSearch: Returns the revision string.
getSearchPercent() - Method in class weka.attributeSelection.RandomSearch: get the percentage of the search space to consider
getSeed() - Method in class weka.attributeSelection.GeneticSearch: get the value of the random number generator's seed
getSeed() - Method in class weka.attributeSelection.RandomSearch
getStartPoint() - Method in class weka.attributeSelection.RankSearch: Get the point at which to start evaluating the ranking
getStartSet() - Method in class weka.attributeSelection.GeneticSearch: Returns a list of attributes (and or attribute ranges) as a String
getStartSet() - Method in class weka.attributeSelection.RandomSearch: Returns a list of attributes (and or attribute ranges) as a String
getStepSize() - Method in class weka.attributeSelection.RankSearch: Get the number of attributes to add from the rankining in each iteration
getTechnicalInformation() - Method in class weka.attributeSelection.GeneticSearch: 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.
getTechnicalInformation() - Method in class weka.attributeSelection.RandomSearch: 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.
getTechnicalInformation() - Method in class weka.attributeSelection.RankSearch: 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.
getVerbose() - Method in class weka.attributeSelection.ExhaustiveSearch: get whether or not output is verbose
getVerbose() - Method in class weka.attributeSelection.RandomSearch: get whether or not output is verbose
globalInfo() - Method in class weka.attributeSelection.ExhaustiveSearch: Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.GeneticSearch: Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.RandomSearch: Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.RankSearch: Returns a string describing this search method

I

improvementThresholdTipText() - Method in class weka.attributeSelection.RankSearch: Returns the tip text for this property

L

listOptions() - Method in class weka.attributeSelection.ExhaustiveSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.GeneticSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.RandomSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.RankSearch: Returns an enumeration describing the available options.

M

maxGenerationsTipText() - Method in class weka.attributeSelection.GeneticSearch: Returns the tip text for this property
mutationProbTipText() - Method in class weka.attributeSelection.GeneticSearch: Returns the tip text for this property

N

nonImprovingAdditionsTipText() - Method in class weka.attributeSelection.RankSearch: Returns the tip text for this property

P

populationSizeTipText() - Method in class weka.attributeSelection.GeneticSearch: Returns the tip text for this property

R

RandomSearch - Class in weka.attributeSelection: RandomSearch :

Performs a Random search in the space of attribute subsets.
RandomSearch() - Constructor for class weka.attributeSelection.RandomSearch: Constructor
RankSearch - Class in weka.attributeSelection: RankSearch :

Uses an attribute/subset evaluator to rank all attributes.
RankSearch() - Constructor for class weka.attributeSelection.RankSearch: Constructor
reportFrequencyTipText() - Method in class weka.attributeSelection.GeneticSearch: Returns the tip text for this property

S

search(ASEvaluation, Instances) - Method in class weka.attributeSelection.ExhaustiveSearch: Searches the attribute subset space using an exhaustive search.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.GeneticSearch: Searches the attribute subset space using a genetic algorithm.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.RandomSearch: Searches the attribute subset space randomly.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.RankSearch: Ranks attributes using the specified attribute evaluator and then searches the ranking using the supplied subset evaluator.
searchPercentTipText() - Method in class weka.attributeSelection.RandomSearch: Returns the tip text for this property
seedTipText() - Method in class weka.attributeSelection.GeneticSearch: Returns the tip text for this property
seedTipText() - Method in class weka.attributeSelection.RandomSearch: Returns the tip text for this property
setAttributeEvaluator(ASEvaluation) - Method in class weka.attributeSelection.RankSearch: Set the attribute evaluator to use for generating the ranking.
setCrossoverProb(double) - Method in class weka.attributeSelection.GeneticSearch: set the probability of crossover
setDebuggingOutput(boolean) - Method in class weka.attributeSelection.RankSearch: Set whether to output debugging info to the console
setExcludeNonImprovingAttributes(boolean) - Method in class weka.attributeSelection.RankSearch: Set whether or not to add prior non-improving attributes when considering more attributes from the ranked list
setImprovementThreshold(double) - Method in class weka.attributeSelection.RankSearch: Set merit improvement threshold
setMaxGenerations(int) - Method in class weka.attributeSelection.GeneticSearch: set the number of generations to evaluate
setMutationProb(double) - Method in class weka.attributeSelection.GeneticSearch: set the probability of mutation
setNonImprovingAdditions(int) - Method in class weka.attributeSelection.RankSearch: Set the number of consecutive non-improving additions to tolerate before terminating the search
setOptions(String[]) - Method in class weka.attributeSelection.ExhaustiveSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.GeneticSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.RandomSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.RankSearch: Parses a given list of options.
setPopulationSize(int) - Method in class weka.attributeSelection.GeneticSearch: set the population size
setReportFrequency(int) - Method in class weka.attributeSelection.GeneticSearch: set how often reports are generated
setSearchPercent(double) - Method in class weka.attributeSelection.RandomSearch: set the percentage of the search space to consider
setSeed(int) - Method in class weka.attributeSelection.GeneticSearch: set the seed for random number generation
setSeed(int) - Method in class weka.attributeSelection.RandomSearch
setStartPoint(int) - Method in class weka.attributeSelection.RankSearch: Set the point at which to start evaluating the ranking
setStartSet(String) - Method in class weka.attributeSelection.GeneticSearch: Sets a starting set of attributes for the search.
setStartSet(String) - Method in class weka.attributeSelection.RandomSearch: Sets a starting set of attributes for the search.
setStepSize(int) - Method in class weka.attributeSelection.RankSearch: Set the number of attributes to add from the rankining in each iteration
setVerbose(boolean) - Method in class weka.attributeSelection.ExhaustiveSearch: set whether or not to output new best subsets as the search proceeds
setVerbose(boolean) - Method in class weka.attributeSelection.RandomSearch: set whether or not to output new best subsets as the search proceeds
startPointTipText() - Method in class weka.attributeSelection.RankSearch: Returns the tip text for this property
startSetTipText() - Method in class weka.attributeSelection.GeneticSearch: Returns the tip text for this property
startSetTipText() - Method in class weka.attributeSelection.RandomSearch: Returns the tip text for this property
stepSizeTipText() - Method in class weka.attributeSelection.RankSearch: Returns the tip text for this property

T

toString() - Method in class weka.attributeSelection.ExhaustiveSearch: prints a description of the search
toString() - Method in class weka.attributeSelection.GeneticSearch: returns a description of the search
toString() - Method in class weka.attributeSelection.RandomSearch: prints a description of the search
toString() - Method in class weka.attributeSelection.RankSearch: returns a description of the search as a String

V

verboseTipText() - Method in class weka.attributeSelection.ExhaustiveSearch: Returns the tip text for this property
verboseTipText() - Method in class weka.attributeSelection.RandomSearch: Returns the tip text for this property

W

weka.attributeSelection - package weka.attributeSelection

A C D E G I L M N P R S T V W