20 citations · 20 across the 2 of their papers we have counts for
2 papers
cs.LG2024
The Explabox: Model-Agnostic Machine Learning Transparency & Analysis
Marcel Robeer, Michiel Bron, Elize Herrewijnen +2
We present the Explabox: an open-source toolkit for transparent and responsible machine learning (ML) model development and usage. Explabox aids in achieving explainable, fair and…
stat.ML2018★ 20 cited
Contrastive Explanations with Local Foil Trees
Jasper van der Waa, Marcel Robeer, Jurriaan van Diggelen +2
Recent advances in interpretable Machine Learning (iML) and eXplainable AI (XAI) construct explanations based on the importance of features in classification tasks. However, in a h…