Subgroup discovery is a data mining task halfway between descriptive and predictive data mining. Nowadays it is very relevant for researchers due to the fact that the knowledge extracted is simple and interesting. For this task, evolutionary fuzzy systems are well suited algorithms because they can find a good trade-off between multiple objectives in large search spaces. In fact, this paper presents the SDEFSR package, which contains all the evolutionary fuzzy systems for subgroup discovery presented throughout the literature. It is a package without dependencies on other software, providing functions with recommended default parameters. In addition, it brings a graphical user interface to avoid the user having to know all the parameters of the algorithms.
rsubgroup, SDEFSR, devtools, mldr
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".
For attribution, please cite this work as
García, et al., "The R Journal: Subgroup Discovery with Evolutionary Fuzzy Systems in R: The SDEFSR Package", The R Journal, 2016
BibTeX citation
@article{RJ-2016-048,
author = {García, Ángel M. and Charte, Francisco and González, Pedro and Carmona, Cristóbal J. and Jesus, María J. del},
title = {The R Journal: Subgroup Discovery with Evolutionary Fuzzy Systems in R: The SDEFSR Package},
journal = {The R Journal},
year = {2016},
note = {https://doi.org/10.32614/RJ-2016-048},
doi = {10.32614/RJ-2016-048},
volume = {8},
issue = {2},
issn = {2073-4859},
pages = {307-323}
}