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Communication Dans Un Congrès Année : 2023

Prime Implicants as a Versatile Tool to Explain Robust Classification

Résumé

In this paper, we investigate how robust classification results can be explained by the notion of prime implicants, focusing on explaining pairwise dominance relations. By robust, we mean that we consider imprecise models that may abstain to classify or to compare two classes when information is insufficient. This will be reflected by considering (convex) sets of probabilities. By prime implicants, we understand a subset of attributes, minimal w.r.t. inclusion, that we need to know or specify before reaching a specified conclusion (either of dominance or non-dominance between two classes). After presenting the general concepts, we derive them in the case of the well-known naive credal classifier.
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Dates et versions

hal-04310960 , version 1 (27-11-2023)

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  • HAL Id : hal-04310960 , version 1

Citer

Hénoïk Willot, Sébastien Destercke, Khaled Belahcene. Prime Implicants as a Versatile Tool to Explain Robust Classification. 13th International Symposium on Imprecise Probabilities: Theories and Applications (ISIPTA 2023), Enrique Miranda; Ignacio Montes; Erik Quaeghebeur; Barbara Vantaggi, Jul 2023, Oviedo, Spain. pp.461-471. ⟨hal-04310960⟩
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