classifier is then used for analyzing the clusters in order to identify which features of the verse metre are critical in cluster assignment [@riid2013determination]. The result is a clear separation of the geographical regions into three well delineated groups but, since no evaluation was performed, it is unclear to what extent the comprehension of how the features lead to the cluster separation is, in fact, interpretable from the user point of view.

Another practical application was presented by Conde-Clemente et al. [-@conde2013interpretable]. A prototype that allows a person with visual disabilities to take their own profile photos was implemented as a fuzzy control system including human-in-the-loop using natural language. The authors argue that, by making use of an approach known as Highly Interpretable Linguistic Knowledge (HILK) methodology, they “are able to represent the extracted knowledge in highly interpretable fuzzy rule-based systems” [@conde2013interpretable]. HILK is a fuzzy modeling methodology intended to produce classifiers easily comprehensible by humans. As in the previously mentioned fuzzy logic approaches, model interpretability is not measured but assumed to be a natural result of the methodology application, where a set of conditions must be met at design time.

**Machine learning** has recently become the most active field 