{ "_id": "6a1037e3acfb0bcc41c9a8b5", "Package": "RoughSets", "Maintainer": "Christoph Bergmeir ", "License": "GPL (>=2)", "Encoding": "UTF-8", "Title": "Data Analysis Using Rough Set and Fuzzy Rough Set Theories", "Authors@R": "c(person(\"Andrzej\", \"Janusz\", role = \"aut\",\nemail = \"janusza@mimuw.edu.pl\"),\nperson(\"Lala Septem\", \"Riza\", role = \"aut\",\nemail = \"lala_s_riza@yahoo.com\"),\nperson(\"Dominik\", \"Ślęzak\", role = \"ctb\"),\nperson(\"Chris\", \"Cornelis\", role = \"ctb\"),\nperson(\"Francisco\", \"Herrera\", role = \"ctb\"),\nperson(\"Jose Manuel\", \"Benitez\", role = \"ctb\"),\nperson(\"Christoph\", \"Bergmeir\", role = c(\"ctb\", \"cre\"),\nemail = \"c.bergmeir@decsai.ugr.es\"),\nperson(\"Sebastian\", \"Stawicki\", role = \"ctb\"))", "Description": "Implementations of algorithms for data analysis based on\nthe rough set theory (RST) and the fuzzy rough set theory\n(FRST). We not only provide implementations for the basic\nconcepts of RST and FRST but also popular algorithms that\nderive from those theories. The methods included in the package\ncan be divided into several categories based on their\nfunctionality: discretization, feature selection, instance\nselection, rule induction and classification based on nearest\nneighbors. RST was introduced by Zdzisław Pawlak in 1982 as a\nsophisticated mathematical tool to model and process imprecise\nor incomplete information. By using the indiscernibility\nrelation for objects/instances, RST does not require additional\nparameters to analyze the data. FRST is an extension of RST.\nThe FRST combines concepts of vagueness and indiscernibility\nthat are expressed with fuzzy sets (as proposed by Zadeh, in\n1965) and RST.", "Version": "1.3-7.1", "URL": "https://github.com/janusza/RoughSets", "Date": "2019-01-24", "RoxygenNote": "7.0.2", "Repository": "https://janusza.r-universe.dev", "Date/Publication": "2020-01-25 18:44:43 UTC", "RemoteUrl": "https://github.com/janusza/roughsets", "RemoteRef": "HEAD", "RemoteSha": "e541657d5bf6dd946af5c777de8ce56da7d4d4cd", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-12 06:09:19 UTC", "User": "root" }, "Author": "Andrzej Janusz [aut],\nLala Septem Riza [aut],\nDominik Ślęzak [ctb],\nChris Cornelis [ctb],\nFrancisco Herrera [ctb],\nJose Manuel Benitez [ctb],\nChristoph Bergmeir [ctb, cre],\nSebastian Stawicki [ctb]", "MD5sum": "44bfb75e0a034c1a97b3b8e07187ab7c", "_user": "janusza", "_type": "src", "_file": "RoughSets_1.3-7.1.tar.gz", "_fileid": "be6d4b271605c86cea9022825067f2e7b899e560e6a13dacaf31768d6926cd39", "_filesize": 831663, "_sha256": "be6d4b271605c86cea9022825067f2e7b899e560e6a13dacaf31768d6926cd39", "_created": "2026-05-12T06:09:19.000Z", "_published": "2026-05-22T11:02:59.372Z", "_distro": "noble", "_jobs": [ { "job": 77366735361, "time": 121, "config": "linux-devel-arm64", "r": "4.7.0", "check": "NOTE", "artifact": "6936943050" }, { "job": 77366734803, "time": 155, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "NOTE", "artifact": "6936952365" }, { "job": 77366735554, "time": 157, "config": "linux-release-arm64", "r": "4.6.0", "check": "NOTE", "artifact": "6936951589" }, { "job": 77366735400, "time": 141, "config": "linux-release-x86_64", "r": "4.6.0", "check": "NOTE", "artifact": "6936948879" }, { "job": 77366735198, "time": 197, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "NOTE", "artifact": "6936964703" }, { "job": 77366735071, "time": 278, "config": "macos-oldrel-x86_64", "r": "4.5.3", "check": "NOTE", "artifact": "6936982336" }, { "job": 77366735348, "time": 210, "config": "macos-release-arm64", "r": "4.6.0", "check": "NOTE", "artifact": "6936963862" }, { "job": 77366735001, "time": 216, "config": "macos-release-x86_64", "r": "4.6.0", "check": "NOTE", "artifact": "6936980460" }, { "job": 77366734847, "time": 166, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "6936912650" }, { "job": 77366734387, "time": 121, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7158939360" }, { "job": 77366734853, "time": 133, "config": "windows-devel", "r": "4.7.0", "check": "NOTE", "artifact": "6936945797" }, { "job": 77366735135, "time": 96, "config": "windows-oldrel", "r": "4.5.3", "check": "NOTE", "artifact": "6936936663" }, { "job": 77366735073, "time": 105, "config": "windows-release", "r": "4.6.0", "check": "NOTE", "artifact": "6936938723" } ], "_buildurl": "https://github.com/r-universe/janusza/actions/runs/25716725974", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/janusza/roughsets", "_commit": { "id": "e541657d5bf6dd946af5c777de8ce56da7d4d4cd", "author": "Andrzej Janusz ", "committer": "Andrzej Janusz ", "message": "adding an experimental method of computing a discernibility matrix plus some performance fixes\n\n- added BC.discernibility.positive.mat.RST\n- some performance optimization to FS.one.reduct.computation\n", "time": 1579977883 }, "_maintainer": { "name": "Christoph Bergmeir", "email": "c.bergmeir@decsai.ugr.es" }, "_registered": true, "_dependencies": [ { "package": "Rcpp", "role": "Depends" }, { "package": "Rcpp", "role": "LinkingTo" }, { "package": "class", "role": "Suggests" } ], "_owner": "janusza", "_selfowned": true, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 38, "_contributors": [ { "user": "janusza", "count": 72, "uuid": 7699724 }, { "user": "cbergmeir", "count": 3, "uuid": 524058 }, { "user": "darekjk", "count": 3, "uuid": 17815942 }, { "user": "fiedukow", "count": 2, "uuid": 297223 } ], "_userbio": { "uuid": 7699724, "type": "user", "name": "Andrzej Janusz" }, "_downloads": { "count": 319, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/RoughSets" }, "_mentions": 2, "_devurl": "https://github.com/janusza/roughsets", "_searchresults": 151, "_topics": [ "cpp" ], "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/RoughSets.html", "manual.pdf" ], "_homeurl": "https://github.com/janusza/roughsets", "_realowner": "janusza", "_cranurl": true, "_releases": [ { "version": "1.0-0", "date": "2014-02-04" }, { "version": "1.1-0", "date": "2014-06-19" }, { "version": "1.2-0", "date": "2015-03-19" }, { "version": "1.2-1", "date": "2015-03-24" }, { "version": "1.3-0", "date": "2015-09-05" }, { "version": "1.3-7", "date": "2019-12-15" }, { "version": "1.3-8", "date": "2024-01-23" } ], "_exports": [ "BC.boundary.reg.RST", "BC.discernibility.mat.FRST", "BC.discernibility.mat.RST", "BC.discernibility.positive.mat.RST", "BC.IND.relation.FRST", "BC.IND.relation.RST", "BC.LU.approximation.FRST", "BC.LU.approximation.RST", "BC.negative.reg.RST", "BC.positive.reg.FRST", "BC.positive.reg.RST", "C.FRNN.FRST", "C.FRNN.O.FRST", "C.POSNN.FRST", "D.discretization.RST", "D.discretize.equal.intervals.RST", "D.discretize.quantiles.RST", "D.global.discernibility.heuristic.RST", "D.local.discernibility.heuristic.RST", "FS.all.reducts.computation", "FS.DAAR.heuristic.RST", "FS.feature.subset.computation", "FS.greedy.heuristic.reduct.RST", "FS.greedy.heuristic.superreduct.RST", "FS.nearOpt.fvprs.FRST", "FS.one.reduct.computation", "FS.permutation.heuristic.reduct.RST", "FS.quickreduct.FRST", "FS.quickreduct.RST", "FS.reduct.computation", "IS.FRIS.FRST", "IS.FRPS.FRST", "MV.conceptClosestFit", "MV.deletionCases", "MV.globalClosestFit", "MV.missingValueCompletion", "MV.mostCommonVal", "MV.mostCommonValResConcept", "RI.AQRules.RST", "RI.CN2Rules.RST", "RI.confidence", "RI.GFRS.FRST", "RI.hybridFS.FRST", "RI.indiscernibilityBasedRules.RST", "RI.laplace", "RI.LEM2Rules.RST", "RI.lift", "RI.support", "SF.applyDecTable", "SF.asDecisionTable", "SF.asFeatureSubset", "SF.read.DecisionTable", "X.entropy", "X.gini", "X.laplace", "X.nOfConflicts", "X.rulesCounting", "X.ruleStrength" ], "_datasets": [ { "name": "RoughSetData", "title": "Data set of the package", "object": "RoughSetData", "file": "RoughSetData.RData", "class": [ "list" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "RoughSets-package", "title": "Getting started with the RoughSets package", "topics": [ "RoughSets-package", "RoughSets" ] }, { "page": "sub-.RuleSetRST", "title": "The '[.' method for '\"RuleSetRST\"' objects", "topics": [ "Extract.RuleSetRST", "[.RuleSetRST" ] }, { "page": "A.Introduction-RoughSets", "title": "Introduction to Rough Set Theory", "topics": [ "A.Introduction-RoughSets", "RoughSets-intro" ] }, { "page": "as.character.RuleSetRST", "title": "The 'as.character' method for RST rule sets", "topics": [ "as.character.RuleSetRST" ] }, { "page": "as.list.RuleSetRST", "title": "The 'as.list' method for RST rule sets", "topics": [ "as.list.RuleSetRST" ] }, { "page": "B.Introduction-FuzzyRoughSets", "title": "Introduction to Fuzzy Rough Set Theory", "topics": [ "B.Introduction-FuzzyRoughSets", "FuzzyRoughSets-intro" ] }, { "page": "BC.boundary.reg.RST", "title": "Computation of a boundary region", "topics": [ "BC.boundary.reg.RST" ] }, { "page": "BC.discernibility.mat.FRST", "title": "The decision-relative discernibility matrix based on fuzzy rough set theory", "topics": [ "BC.discernibility.mat.FRST" ] }, { "page": "BC.discernibility.mat.RST", "title": "Computation of a decision-relative discernibility matrix based on the rough set theory", "topics": [ "BC.discernibility.mat.RST" ] }, { "page": "BC.discernibility.positive.mat.RST", "title": "Computation of a positive decision-relative discernibility matrix based on the rough set theory", "topics": [ "BC.discernibility.positive.mat.RST" ] }, { "page": "BC.IND.relation.FRST", "title": "The indiscernibility relation based on fuzzy rough set theory", "topics": [ "BC.IND.relation.FRST" ] }, { "page": "BC.IND.relation.RST", "title": "Computation of indiscernibility classes based on the rough set theory", "topics": [ "BC.IND.relation.RST" ] }, { "page": "BC.LU.approximation.FRST", "title": "The fuzzy lower and upper approximations based on fuzzy rough set theory", "topics": [ "BC.LU.approximation.FRST" ] }, { "page": "BC.LU.approximation.RST", "title": "Computation of lower and upper approximations of decision classes", "topics": [ "BC.LU.approximation.RST" ] }, { "page": "BC.negative.reg.RST", "title": "Computation of a negative region", "topics": [ "BC.negative.reg.RST" ] }, { "page": "BC.positive.reg.FRST", "title": "Positive region based on fuzzy rough set", "topics": [ "BC.positive.reg.FRST" ] }, { "page": "BC.positive.reg.RST", "title": "Computation of a positive region", "topics": [ "BC.positive.reg.RST" ] }, { "page": "C.FRNN.FRST", "title": "The fuzzy-rough nearest neighbor algorithm", "topics": [ "C.FRNN.FRST" ] }, { "page": "C.FRNN.O.FRST", "title": "The fuzzy-rough ownership nearest neighbor algorithm", "topics": [ "C.FRNN.O.FRST" ] }, { "page": "C.POSNN.FRST", "title": "The positive region based fuzzy-rough nearest neighbor algorithm", "topics": [ "C.POSNN.FRST" ] }, { "page": "D.discretization.RST", "title": "The wrapper function for discretization methods", "topics": [ "D.discretization.RST" ] }, { "page": "D.discretize.equal.intervals.RST", "title": "Unsupervised discretization into intervals of equal length.", "topics": [ "D.discretize.equal.intervals.RST" ] }, { "page": "D.discretize.quantiles.RST", "title": "The quantile-based discretization", "topics": [ "D.discretize.quantiles.RST" ] }, { "page": "D.global.discernibility.heuristic.RST", "title": "Supervised discretization based on the maximum discernibility heuristic", "topics": [ "D.global.discernibility.heuristic.RST" ] }, { "page": "D.local.discernibility.heuristic.RST", "title": "Supervised discretization based on the local discernibility heuristic", "topics": [ "D.local.discernibility.heuristic.RST" ] }, { "page": "FS.all.reducts.computation", "title": "A function for computing all decision reducts of a decision system", "topics": [ "FS.all.reducts.computation" ] }, { "page": "FS.DAAR.heuristic.RST", "title": "The DAAR heuristic for computation of decision reducts", "topics": [ "FS.DAAR.heuristic.RST" ] }, { "page": "FS.feature.subset.computation", "title": "The superreduct computation based on RST and FRST", "topics": [ "FS.feature.subset.computation" ] }, { "page": "FS.greedy.heuristic.reduct.RST", "title": "The greedy heuristic algorithm for computing decision reducts and approximate decision reducts", "topics": [ "FS.greedy.heuristic.reduct.RST" ] }, { "page": "FS.greedy.heuristic.superreduct.RST", "title": "The greedy heuristic method for determining superreduct based on RST", "topics": [ "FS.greedy.heuristic.superreduct.RST" ] }, { "page": "FS.nearOpt.fvprs.FRST", "title": "The near-optimal reduction algorithm based on fuzzy rough set theory", "topics": [ "FS.nearOpt.fvprs.FRST" ] }, { "page": "FS.one.reduct.computation", "title": "Computing one reduct from a discernibility matrix", "topics": [ "FS.one.reduct.computation" ] }, { "page": "FS.permutation.heuristic.reduct.RST", "title": "The permutation heuristic algorithm for computation of a decision reduct", "topics": [ "FS.permutation.heuristic.reduct.RST" ] }, { "page": "FS.quickreduct.FRST", "title": "The fuzzy QuickReduct algorithm based on FRST", "topics": [ "FS.quickreduct.FRST" ] }, { "page": "FS.quickreduct.RST", "title": "QuickReduct algorithm based on RST", "topics": [ "FS.quickreduct.RST" ] }, { "page": "FS.reduct.computation", "title": "The reduct computation methods based on RST and FRST", "topics": [ "FS.reduct.computation" ] }, { "page": "IS.FRIS.FRST", "title": "The fuzzy rough instance selection algorithm", "topics": [ "IS.FRIS.FRST" ] }, { "page": "IS.FRPS.FRST", "title": "The fuzzy rough prototype selection method", "topics": [ "IS.FRPS.FRST" ] }, { "page": "MV.conceptClosestFit", "title": "Concept Closest Fit", "topics": [ "MV.conceptClosestFit" ] }, { "page": "MV.deletionCases", "title": "Missing value completion by deleting instances", "topics": [ "MV.deletionCases" ] }, { "page": "MV.globalClosestFit", "title": "Global Closest Fit", "topics": [ "MV.globalClosestFit" ] }, { "page": "MV.missingValueCompletion", "title": "Wrapper function of missing value completion", "topics": [ "MV.missingValueCompletion" ] }, { "page": "MV.mostCommonVal", "title": "Replacing missing attribute values by the attribute mean or common values", "topics": [ "MV.mostCommonVal" ] }, { "page": "MV.mostCommonValResConcept", "title": "The most common value or mean of an attribute restricted to a concept", "topics": [ "MV.mostCommonValResConcept" ] }, { "page": "predict.RuleSetFRST", "title": "The predicting function for rule induction methods based on FRST", "topics": [ "predict.FRST", "predict.RuleSetFRST" ] }, { "page": "predict.RuleSetRST", "title": "Prediction of decision classes using rule-based classifiers.", "topics": [ "predict.RST", "predict.RuleSetRST" ] }, { "page": "print.FeatureSubset", "title": "The print method of FeatureSubset objects", "topics": [ "print.FeatureSubset" ] }, { "page": "print.RuleSetRST", "title": "The print function for RST rule sets", "topics": [ "print.RuleSetRST" ] }, { "page": "RI.AQRules.RST", "title": "Rule induction using the AQ algorithm", "topics": [ "RI.AQRules.RST" ] }, { "page": "RI.CN2Rules.RST", "title": "Rule induction using a version of CN2 algorithm", "topics": [ "RI.CN2Rules.RST" ] }, { "page": "RI.GFRS.FRST", "title": "Generalized fuzzy rough set rule induction based on FRST", "topics": [ "RI.GFRS.FRST" ] }, { "page": "RI.hybridFS.FRST", "title": "Hybrid fuzzy-rough rule and induction and feature selection", "topics": [ "RI.hybridFS.FRST" ] }, { "page": "RI.indiscernibilityBasedRules.RST", "title": "Rule induction from indiscernibility classes.", "topics": [ "RI.indiscernibilityBasedRules.RST" ] }, { "page": "RI.laplace", "title": "Quality indicators of RST decision rules", "topics": [ "RI.confidence", "RI.laplace", "RI.lift", "RI.support" ] }, { "page": "RI.LEM2Rules.RST", "title": "Rule induction using the LEM2 algorithm", "topics": [ "RI.LEM2Rules.RST" ] }, { "page": "RoughSetData", "title": "Data set of the package", "topics": [ "RoughSetData" ] }, { "page": "SF.applyDecTable", "title": "Apply for obtaining a new decision table", "topics": [ "SF.applyDecTable" ] }, { "page": "SF.asDecisionTable", "title": "Converting a data.frame into a 'DecisionTable' object", "topics": [ "SF.asDecisionTable" ] }, { "page": "SF.asFeatureSubset", "title": "Converting custom attribute name sets into a FeatureSubset object", "topics": [ "SF.asFeatureSubset" ] }, { "page": "SF.read.DecisionTable", "title": "Reading tabular data from files.", "topics": [ "SF.read.DecisionTable" ] }, { "page": "summary.IndiscernibilityRelation", "title": "The summary function for an indiscernibility relation", "topics": [ "summary.IndiscernibilityRelation" ] }, { "page": "summary.LowerUpperApproximation", "title": "The summary function of lower and upper approximations based on RST and FRST", "topics": [ "summary.LowerUpperApproximation" ] }, { "page": "summary.PositiveRegion", "title": "The summary function of positive region based on RST and FRST", "topics": [ "summary.PositiveRegion" ] }, { "page": "summary.RuleSetFRST", "title": "The summary function of rules based on FRST", "topics": [ "summary.RuleSetFRST" ] }, { "page": "summary.RuleSetRST", "title": "The summary function of rules based on RST", "topics": [ "summary.RuleSetRST" ] }, { "page": "X.entropy", "title": "The entropy measure", "topics": [ "X.entropy" ] }, { "page": "X.gini", "title": "The gini-index measure", "topics": [ "X.gini" ] }, { "page": "X.laplace", "title": "Rule voting by the Laplace estimate", "topics": [ "X.laplace" ] }, { "page": "X.nOfConflicts", "title": "The discernibility measure", "topics": [ "X.nOfConflicts" ] }, { "page": "X.rulesCounting", "title": "Rule voting by counting matching rules", "topics": [ "X.rulesCounting" ] }, { "page": "X.ruleStrength", "title": "Rule voting by strength of the rule", "topics": [ "X.ruleStrength" ] } ], "_rundeps": [ "Rcpp" ], "_sysdeps": [ { "shlib": "libstdc++", "package": "libstdc++6", "source": "gcc", "version": "14.2.0-4ubuntu2~24.04.1", "name": "c++", "homepage": "http://gcc.gnu.org/", "description": "GNU Standard C++ Library v3" } ], "_score": 5.536911794293624, "_indexed": true, "_nocasepkg": "roughsets", "_universes": [ "janusza" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.3-7.1", "date": 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