Towards a Generic Framework for Black-box Explanations of Algorithmic Decision Systems
Abstract
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.
Origin | Files produced by the author(s) |
---|
Loading...