RT Journal Article
T1 How to Build Self-Explaining Fuzzy Systems: From Interpretability to Explainability
A1 Stepin, Ilia
A1 Suffian, Muhammad
A1 Catalá Bolós, Alejandro
A1 Alonso Moral, José María
AB Fuzzy systems are known to provide not only accurate but also interpretable predictions. However, their explainability may be undermined if non-semantically grounded linguistic terms are used. Additional non-trivial challenges would arise if a prediction were to be explained counterfactually, i.e., in terms of hypothetical, non-predicted outputs. In this paper, we explore how both factual and counterfactual automated explanations can justify the output of fuzzy rule-based classifiers, and thus contribute to making them more trustworthy. Moreover, we demonstrate how end user preferences can be handled by customizing automated explanations, making them interactive, personalized, and therefore, human-centric. The full immersive article at IEEE Xplore provides detailed interactive examples for better understanding.
PB IEEE
SN 1556-603X
YR 2024
FD 2024
LK https://hdl.handle.net/10347/42565
UL https://hdl.handle.net/10347/42565
LA eng
NO I. Stepin, M. Suffian, A. Catala and J. M. Alonso-Moral, "How to Build Self-Explaining Fuzzy Systems: From Interpretability to Explainability [AI-eXplained]," in IEEE Computational Intelligence Magazine, vol. 19, no. 1, pp. 81-82, Feb. 2024, doi: 10.1109/MCI.2023.3328098
NO I. Stepin is an FPI researcher (Grant PRE2019-090153). M. Suffian is a PhD researcher (Matricola N.309445, funded by University of Urbino, Italy). This work is also supported by Grant PID2021-123152OB-C21 funded by MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future”, Grant TED2021-130295B-C33 funded by MCIN/AEI/10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR”, and the Galician Ministry of Culture, Education, Professional Training and University (grants ED431G2019/04 and ED431C2022/19 co-funded by the European Regional Development Fund, ERDF/FEDER program).
DS Minerva
RD 9 jun 2026