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 DOI: 10.32614/CRAN.package.SDEFSR 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: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=SDEFSR to link to this page.
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