RITUAL: a Platform Quantifying the Trustworthiness of Supervised Machine Learning
Alberto Huertas Celdrán, Jan Bauer, Melike Demirci, Joel Leupp, Muriel Figueredo Franco, Pedro Miguel Sánchez Sánchez, Gérôme Bovet, Gregorio Martínez Pérez, Burkhard Stiller · 2022
This demo presents RITUAL, a platform composed of a novel algorithm and a Web application quantifying the trustworthiness level of supervised Machine and Deep Learning (ML/DL) models according to their fairness, explainability, robustness, and accountability. The algorithm is deployed on a Web application to allow users to quantify and compare the trustworthiness of their ML/DL models. Finally, a scenario with ML/DL models classifying network cyberattacks demonstrates the platform applicability.