# Man pages for lucasbyAI/RoughSetsData Analysis Using Rough Set and Fuzzy Rough Set Theories

 A.Introduction-RoughSets Introduction to Rough Set Theory as.character.RuleSetRST The 'as.character' method for RST rule sets as.list.RuleSetRST The 'as.list' method for RST rule sets BC.discernibility.mat.FRST The decision-relative discernibility matrix based on fuzzy... BC.discernibility.mat.RST Computation of a decision-relative discernibility matrix... BC.IND.relation.FRST The indiscernibility relation based on fuzzy rough set theory BC.IND.relation.RST Computation of indiscernibility classes based on the rough... BC.LU.approximation.FRST The fuzzy lower and upper approximations based on fuzzy rough... BC.LU.approximation.RST Computation of lower and upper approximations of decision... BC.positive.reg.FRST Positive region based on fuzzy rough set BC.positive.reg.RST Computation of a positive region B.Introduction-FuzzyRoughSets Introduction to Fuzzy Rough Set Theory C.FRNN.FRST The fuzzy-rough nearest neighbor algorithm C.FRNN.O.FRST The fuzzy-rough ownership nearest neighbor algorithm C.POSNN.FRST The positive region based fuzzy-rough nearest neighbor... D.discretization.RST The wrapper function for discretization methods D.discretize.equal.intervals.RST Unsupervised discretization into intervals of equal length. D.discretize.quantiles.RST The quantile-based discretization D.global.discernibility.heuristic.RST Supervised discretization based on the maximum discernibility... D.local.discernibility.heuristic.RST Supervised discretization based on the local discernibility... FS.all.reducts.computation A function for computing all decision reducts of a decision... FS.DAAR.heuristic.RST The DAAR heuristic for computation of decision reducts FS.feature.subset.computation The superreduct computation based on RST and FRST FS.greedy.heuristic.reduct.RST The greedy heuristic algorithm for computing decision reducts... FS.greedy.heuristic.superreduct.RST The greedy heuristic method for determining superreduct based... FS.nearOpt.fvprs.FRST The near-optimal reduction algorithm based on fuzzy rough set... FS.one.reduct.computation Computing one reduct from a discernibility matrix FS.permutation.heuristic.reduct.RST The permutation heuristic algorithm for computation of a... FS.quickreduct.FRST The fuzzy QuickReduct algorithm based on FRST FS.quickreduct.RST QuickReduct algorithm based on RST FS.reduct.computation The reduct computation methods based on RST and FRST IS.FRIS.FRST The fuzzy rough instance selection algorithm IS.FRPS.FRST The fuzzy rough prototype selection method MV.conceptClosestFit Concept Closest Fit MV.deletionCases Missing value completion by deleting instances MV.globalClosestFit Global Closest Fit MV.missingValueCompletion Wrapper function of missing value completion MV.mostCommonVal Replacing missing attribute values by the attribute mean or... MV.mostCommonValResConcept The most common value or mean of an attribute restricted to a... predict.RuleSetFRST The predicting function for rule induction methods based on... predict.RuleSetRST Prediction of decision classes using rule-based classifiers. print.FeatureSubset The print method of FeatureSubset objects print.RuleSetRST The print function for RST rule sets RI.AQRules.RST Rule induction using the AQ algorithm RI.CN2Rules.RST Rule induction using a version of CN2 algorithm RI.GFRS.FRST Generalized fuzzy rough set rule induction based on FRST RI.hybridFS.FRST Hybrid fuzzy-rough rule and induction and feature selection RI.indiscernibilityBasedRules.RST Rule induction from indiscernibility classes. RI.laplace Quality indicators of RST decision rules RI.LEM2Rules.RST Rule induction using the LEM2 algorithm RoughSetData Data set of the package RoughSets-package Getting started with the RoughSets package SF.applyDecTable Apply for obtaining a new decision table SF.asDecisionTable Converting a data.frame into a 'DecisionTable' object SF.asFeatureSubset Converting custom attribute name sets into a FeatureSubset... SF.read.DecisionTable Reading tabular data from files. sub-.RuleSetRST The '[.' method for '"RuleSetRST"' objects summary.IndiscernibilityRelation The summary function for an indiscernibility relation summary.LowerUpperApproximation The summary function of lower and upper approximations based... summary.PositiveRegion The summary function of positive region based on RST and FRST summary.RuleSetFRST The summary function of rules based on FRST summary.RuleSetRST The summary function of rules based on RST X.entropy The entropy measure X.gini The gini-index measure X.laplace Rule voting by the Laplace estimate X.nOfConflicts The discernibility measure X.rulesCounting Rule voting by counting matching rules X.ruleStrength Rule voting by strength of the rule
lucasbyAI/RoughSets documentation built on May 21, 2017, 3:38 p.m.