Relating decision rules and attribute implications

  1. Fernando Chacón-Gómez 1
  2. M. Eugenia Cornejo 1
  3. Jesús Medina 1
  1. 1 Department of Mathematics, University of Cádiz, Cádiz, Spain
Proceedings:
The 16th International Conference on Concept Lattices and Their Applications, CLA 2022, Tallinn, Estonia, June 20–22, 2022, Proceedings

Publisher: CEUR Workshop Proceedings

Year of publication: 2022

Pages: 69-78

Type: Conference paper

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Abstract

Formal Concept Analysis (FCA) and Rough Set Theory (RST) are two useful mathematical tools forextracting information, which have different philosophies. One important issue in data science is toobtain relationships among the main variables in the considered data set. Both theories, FCA and RST,independently study these relations by means of attribute implications in FCA and decision rules in RST.This paper introduces a preliminary comparison between these approaches, focused on the notions ofvalid attribute implication in FCA and true decision rule in RST.