Logics for Binary-input Classifiers and Their Explanations
Résumé
We present our work [1, 2] on modal logics for binary-input classifiers and their explanations. They are able to represent classifiers that propositional logic cannot. In particular, black box classifier is understood as uncertainty among admissible classifiers which are coherent with an agent's partial knowledge, and represented in a product modal logic framework. We also briefly show the logics' application to XAI.
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