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:
Downloads:
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