to formalize linguistic propositions which are likely to be easily understood by human beings”. But they also point out that, besides being a feature taken for granted even inside the fuzzy community, interpretability is not an intrinsic property of fuzzy models. Although fuzzy logic has a natural inclination to interpretability, whether every element in a fuzzy system can be checked and understood by a human being heavily depends on how the system is designed [@alonso2011special].

Mencar et al. [-@mencar2011interpretability] define fuzzy model interpretability as a relation between *fuzzy sets* – the basic elements of a fuzzy rule base – and *concepts* – basic units of human knowledge. Fuzzy sets and concepts are linked by the common linguistic terms they refer to, so a fuzzy model can be said interpretable when its explicit semantics, that is, the linguistic representation of fuzzy sets, is cointensive with its implicit semantics inferred by a human, i.e., the meanings they infer while reading the linguistic representation of the rules [@mencar2011interpretability].

As the knowledge extracted from data by fuzzy systems must be usually communicated to users, the fuzzy community has been, in recent years, taking into account interpretability issues as a major research concern [@alonso2014some]. Balázs 