Prometheus: Harnessing Fuzzy Logic and Natural Language for Human-centric Explainable Artificial Intelligence

TítuloPrometheus: Harnessing Fuzzy Logic and Natural Language for Human-centric Explainable Artificial Intelligence
AutoresEttore Mariotti, Jose M. Alonso-Moral, Albert Gatt
TipoComunicación para congreso
Fonte XX Spanish Congress on Fuzzy Logic and Technologies, Málaga, España, 2021.
AbstractPrometheus is an interpretable model which is suitable for the generation of visual and textual explanations grounded in common sense knowledge. This model can be seen as a special case of generalized additive models, which can be also interpreted as a list of (fuzzy) rules. The goodness of the model is illustrated with one benchmark dataset from the medical domain. Reported results are encouraging. They suggest that Prometheus exhibits a good balance between understandability and classification performance in comparison with other well-known models (e.g., linear models, decision trees or fuzzy rule-based classifiers) which are deemed as interpretable.
Palabras chaveXAI, Interpretable ML, Shapley Values, Generalized Additive Models, Fuzzy Logic