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 set theory
BC.LU.approximation.FRST
                        The fuzzy lower and upper approximations based
                        on fuzzy rough set theory
BC.LU.approximation.RST
                        Computation of lower and upper approximations
                        of decision classes
BC.boundary.reg.RST     Computation of a boundary region
BC.discernibility.mat.FRST
                        The decision-relative discernibility matrix
                        based on fuzzy rough set theory
BC.discernibility.mat.RST
                        Computation of a decision-relative
                        discernibility matrix based on the rough set
                        theory
BC.negative.reg.RST     Computation of a negative region
BC.positive.reg.FRST    Positive region based on fuzzy rough set
BC.positive.reg.RST     Computation of a positive region
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 algorithm
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 heuristic
D.local.discernibility.heuristic.RST
                        Supervised discretization based on the local
                        discernibility heuristic
FS.DAAR.heuristic.RST   The DAAR heuristic for computation of decision
                        reducts
FS.all.reducts.computation
                        A function for computing all decision reducts
                        of a decision system
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 and approximate decision
                        reducts
FS.greedy.heuristic.superreduct.RST
                        The greedy heuristic method for determining
                        superreduct based on RST
FS.nearOpt.fvprs.FRST   The near-optimal reduction algorithm based on
                        fuzzy rough set theory
FS.one.reduct.computation
                        Computing one reduct from a discernibility
                        matrix
FS.permutation.heuristic.reduct.RST
                        The permutation heuristic algorithm for
                        computation of a decision reduct
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 common values
MV.mostCommonValResConcept
                        The most common value or mean of an attribute
                        restricted to a concept
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.LEM2Rules.RST        Rule induction using the LEM2 algorithm
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
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 object
SF.read.DecisionTable   Reading tabular data from files.
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.ruleStrength          Rule voting by strength of the rule
X.rulesCounting         Rule voting by counting matching rules
[.RuleSetRST            The '[.' method for '"RuleSetRST"' objects
as.character.RuleSetRST
                        The 'as.character' method for RST rule sets
as.list.RuleSetRST      The 'as.list' method for RST rule sets
predict.RuleSetFRST     The predicting function for rule induction
                        methods based on FRST
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
summary.IndiscernibilityRelation
                        The summary function for an indiscernibility
                        relation
summary.LowerUpperApproximation
                        The summary function of lower and upper
                        approximations based on RST and FRST
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
