habermanRules

<p>Rules generated by the SDIGA algorithm with the default parameters for the <code>haberman</code> dataset.</p>

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. Gonz<c3><a1>lez, 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.

Angel M. Garcia

SDEFSR

Subgroup Discovery with Evolutionary Fuzzy Systems

Pedro Gonzalez

Cristobal J. Carmona

Francisco Charte

Maria J. del Jesus

habermanRules function

Haberman survival rule set — habermanRules

Haberman survival rule set

habermanRules: Haberman survival rule set

Description

Arguments

Details

Examples