Towards a Generic Framework for Black-box Explanations of Algorithmic Decision Systems
Résumé
The main goal of this paper is to define a generic framework for black-box explanation methods in order to make it easier to compare and classify different approaches. We focus on two components of this framework, called respectively “Sampling” and “Generation”, which are characterized formally and used to build a taxonomy of explanation methods. This document gives details on how this framework can be used to describe black-box explanation methods found in the literature.
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