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

Authors: Mariotti, Ettore; Moral, Jose Maria Alonso; Gatt, Albert;

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

Abstract

Prometheus 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.

Keywords

Interpretable Machine Learning, Shapley Values, Explainable Artificial Intelligence, Generalized Additive Models, Fuzzy Rule-based Classifiers

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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