most citedX-SHAP: towards multiplicative explainability of Machine Learning

5 citations · 5 across the 1 of their papers we have counts for

collaborators

1 paper

cs.LG2020★ 5 cited

X-SHAP: towards multiplicative explainability of Machine Learning

Luisa Bouneder, Yannick Léo, Aimé Lachapelle

This paper introduces X-SHAP, a model-agnostic method that assesses multiplicative contributions of variables for both local and global predictions. This method theoretically and o…