Data 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 |

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