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Constrained Interval Type-2 Fuzzy Classification Systems for Explainable AI (XAI)

D'Alterio, Pasquale ; Garibaldi, Jonathan M.; John, Robert I.

Authors

Pasquale D'Alterio

Robert I. John



Abstract

In recent year, there has been a growing need for intelligent systems that not only are able to provide reliable classifications but can also produce explanations for the decisions they make. The demand for increased explainability has led to the emergence of explainable artificial intelligence (XAI) as a specific research field. In this context, fuzzy logic systems represent a promising tool thanks to their inherently interpretable structure. The use of a rule-base and linguistic terms, in fact, have allowed researchers to create models that are able to produce explanations in natural language for each of the classifications they make. So far, however, designing systems that make use of interval type-2 (IT2) fuzzy logic and also give explanations for their outputs has been very challenging, partially due to the presence of the type-reduction step. In this paper, it will be shown how constrained interval type-2 (CIT2) fuzzy sets represent a valid alternative to conventional interval type-2 sets in order to address this issue. Through the analysis of two case studies from the medical domain, it is shown how explainable CIT2 classifiers are produced. These systems can explain which rules contributed to the creation of each of the endpoints of the output interval centroid, while showing (in these examples) the same level of accuracy as their IT2 counterpart.

Citation

D'Alterio, P., Garibaldi, J. M., & John, R. I. (2020). Constrained Interval Type-2 Fuzzy Classification Systems for Explainable AI (XAI). In Proceedings of IEEE World Congress on Computational Intelligence (WCCI) 2020

Conference Name IEEE World Congress on Computational Intelligence (WCCI) 2020
Start Date Jul 19, 2020
End Date Jul 24, 2020
Acceptance Date Mar 20, 2020
Online Publication Date Jul 24, 2020
Publication Date Jul 24, 2020
Deposit Date Aug 10, 2020
Publicly Available Date Aug 10, 2020
Book Title Proceedings of IEEE World Congress on Computational Intelligence (WCCI) 2020
Keywords Index Terms-Constrained interval type-2; XAI; explainable type-2 fuzzy systems
Public URL https://nottingham-repository.worktribe.com/output/4825085
Additional Information © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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