1 code implementation • 13 Jan 2023 • Surin Ahn, Justin Grana, Yafet Tamene, Kristian Holsheimer
We present a model-agnostic algorithm for generating post-hoc explanations and uncertainty intervals for a machine learning model when only a static sample of inputs and outputs from the model is available, rather than direct access to the model itself.