Demo: an interactive visualization combining rule-based and feature importance explanations

The Human-Computer Interaction (HCI) community has long stressed the need for a more user-centered approach to Explainable Artificial Intelligence (XAI), a research area that aims at defining algorithms and tools to illustrate the predictions of the so-called black-box models. This approach can benefit from the fields of user-interface, user experience, and visual analytics. In this demo, we propose a visual-based tool, "F.I.P.E.R.", that shows interactive explanations combining rules and feature importance.