Fast Hierarchical Games for Image Explanations.

As modern complex neural networks keep breaking records and solving harder problems, their predictions also become less and less intelligible. The current lack of interpretability often undermines the deployment of accurate machine learning tools in sensitive settings. In this work, we present a model-agnostic explanation method for image classification based on a hierarchical extension of Shapley coefficients-Hierarchical Shap (h-Shap)-that resolves some of the limitations of current approaches.