SDEFSR: Subgroup Discovery with Evolutionary Fuzzy Systems

Implementation of evolutionary fuzzy systems for the data mining task called "subgroup discovery". In particular, the algorithms presented in this package are: M. J. del Jesus, P. Gonzalez, F. Herrera, M. Mesonero (2007) <doi:10.1109/TFUZZ.2006.890662> M. J. del Jesus, P. Gonzalez, F. Herrera (2007) <doi:10.1109/MCDM.2007.369416> C. J. Carmona, P. Gonzalez, M. J. del Jesus, F. Herrera (2010) <doi:10.1109/TFUZZ.2010.2060200> C. J. Carmona, V. Ruiz-Rodado, M. J. del Jesus, A. Weber, M. Grootveld, P. González, D. Elizondo (2015) <doi:10.1016/j.ins.2014.11.030> It also provide a Shiny App to ease the analysis. The algorithms work with data sets provided in KEEL, ARFF and CSV format and also with data.frame objects.

Version: 0.7.22
Depends: R (≥ 3.0.0)
Imports: foreign, methods, parallel, stats, utils, ggplot2, shiny (≥ 0.11)
Suggests: knitr, rmarkdown
Published: 2021-04-30
Author: Angel M. Garcia [aut, cre], Pedro Gonzalez [aut, cph], Cristobal J. Carmona [aut, cph], Francisco Charte [ctb], Maria J. del Jesus [aut, cph]
Maintainer: Angel M. Garcia <agvico at ujaen.es>
License: LGPL (≥ 3)
URL: https://github.com/SIMIDAT/SDEFSR
NeedsCompilation: no
Materials: NEWS
CRAN checks: SDEFSR results

Documentation:

Reference manual: SDEFSR.pdf
Vignettes: Subgroup Discovery with Evolutionary Fuzzy Systems in R: the SDEFSR Package

Downloads:

Package source: SDEFSR_0.7.22.tar.gz
Windows binaries: r-devel: SDEFSR_0.7.22.zip, r-release: SDEFSR_0.7.22.zip, r-oldrel: SDEFSR_0.7.22.zip
macOS binaries: r-release (arm64): SDEFSR_0.7.22.tgz, r-release (x86_64): SDEFSR_0.7.22.tgz, r-oldrel: SDEFSR_0.7.22.tgz
Old sources: SDEFSR archive

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