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RoughSets

1.3-8Package record

Data Analysis Using Rough Set and Fuzzy Rough Set Theories

0packages depend
4.8Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Implementations of algorithms for data analysis based on the rough set theory (RST) and the fuzzy rough set theory (FRST). We not only provide implementations for the basic concepts of RST and FRST but also popular algorithms that derive from those theories. The methods included in the package can be divided into several categories based on their functionality: discretization, feature selection, instance selection, rule induction and classification based on nearest neighbors. RST was introduced by Zdzisław Pawlak in 1982 as a sophisticated mathematical tool to model and process imprecise or incomplete information. By using the indiscernibility relation for objects/instances, RST does not require additional parameters to analyze the data. FRST is an extension of RST. The FRST combines concepts of vagueness and indiscernibility that are expressed with fuzzy sets (as proposed by Zadeh, in 1965) and RST.

Install

Health

CRAN checks
13OK
Slowest check: 3.4 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-09-08
  • ERROR12 OK, 1 ERROR2026-09-07
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-04-22
Show 2 earlier changesHide 2 earlier changes
  • ERROR13 OK, 1 ERROR2026-04-18
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.3-8
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
68includes a package overview page
Examples that run
100%61 run in a plain check
Exported functions with examples
89%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
62%

Also includes 29 demo scripts (run with demo())

Downloads

4.8K
CRAN downloads in the past year
Rank #8,243 · ~13/day · ~399/mo
Daily download trend is not available in this view yet.
36630 days
1.1K90 days
4.8K1 year
Compare downloads with other packages →
Also on363 r2u5 autocran2.5K conda_forge159 c2d4u

Repository

38Stars
13Forks
3Open issues
0Open PRs
0Releases
80Commits
4Commit identities
80 commits · Last activity 2020-01-25 · 0% stars, 30d · The default branch showed an older version (1.3-7.1) than CRAN on 2026-10-21
Responsiveness
How these are sampled
PRs merged (all time)
100%
Median days to close, 50 most recently updated closed issues
42
Median days to close, 50 most recently updated closed PRs
9

Stars over time

2024-10-26 · 362026-07-07 · 38
PracticesBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/janusza/roughsets on 2026-10-21.

Git structural (1)
.gitattributes
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
2 external dependencies (excludes base and recommended)

Installing RoughSets adds 1 package (1 with compiled code, 1.8 MB of source tarballs). Heaviest: Rcpp 1.8 MB.

Depends (1)
Imports (0)
none
LinkingTo (1)
Suggests (1)
class
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (8)
Contributor, Maintainer · added in 1.2-0
Contributor
Contributor · added in 1.2-0
Contributor

Maintainer since 1.0-0 (2014)

Listed in earlier versions (1)
Dominik Slezak
no longer listed · 1.0-0 to 1.1-0
Releases (7)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 1.3-8Latest
    record
    2024-01-23 · current release · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • 1.3-7
    record
    2019-12-15 · diff ↗ ·
    added 2 exports
    BC.boundary.reg.RST, BC.negative.reg.RST
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
  • R
    R 3.3.0 released · 2016-05-03
  • 1.3-0
    record
    2015-09-05 · diff ↗ ·
    removed 2 exports
    D.local.discernibility.matrix.RST, D.max.discernibility.matrix.RST
    added 5 exports
    D.local.discernibility.heuristic.RST, RI.confidence, RI.laplace, RI.lift, RI.support
  • R
    R 3.2.0 released · 2015-04-16
  • 1.2-1
    record
    2015-03-24 · diff ↗
Show 5 earlier eventsHide 5 earlier events
  • 1.2-0
    record
    2015-03-19 · diff ↗ ·
    removed 3 exports
    X.bestFirst, X.nOfConflictsLog, X.nOfConflictsSqrt
    added 8 exports
    FS.DAAR.heuristic.RST, RI.AQRules.RST, RI.CN2Rules.RST, RI.LEM2Rules.RST, SF.asFeatureSubset, X.laplace, X.ruleStrength, X.rulesCounting
  • 1.1-0
    record
    2014-06-19 · diff ↗ ·
    added 8 exports
    FS.one.reduct.computation, MV.conceptClosestFit, MV.deletionCases, MV.globalClosestFit, MV.missingValueCompletion, MV.mostCommonVal, MV.mostCommonValResConcept, SF.read.DecisionTable
  • R
    R 3.1.0 released · 2014-04-10
  • 1.0-0
    record
    2014-02-04
  • R
    R 3.0.0 released · 2013-04-03

Package metadata

First published
2014-02-04
Total releases
7 / 12 yrs
License
GPL (>= 2) OSI
Bundled data
42 KB / 1 file
Download size
229 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("RoughSets")
Bergmeir, C., Benitez, J. M., Cornelis, C., Herrera, F., Janusz, A., Riza, L. S., Stawicki, S., & Ślęzak, D. (2024). RoughSets: Data Analysis Using Rough Set and Fuzzy Rough Set Theories (Version 1.3-8) [Computer software]. https://doi.org/10.32614/CRAN.package.RoughSets

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for RoughSets version 1.3-8 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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