Assessing the Interpretability of Fuzzy Rule Bases
Résumé
Fuzzy systems are valued for their ability to model complex phenomena while contributing to maintaining interpretability through natural language rules. However, this property is not inherently guaranteed by the adoption of fuzzy sets. This paper proposes both a tool, named FuzzIC, to assess the interpretability of fuzzy rule bases through the computation of various complementary criteria taken from the literature, and an empirical user study of these criteria. The latter shows that some criteria capture characteristics that significantly enhance interpretability in practical applications, while others appear less influential than anticipated.
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