38 citations · 50 across the 10 of their papers we have counts for
3 papers · 1 filter
Evaluating machine learning models in non-standard settings: An overview and new findings
Roman Hornung, Malte Nalenz, Lennart Schneider +5
Estimating the generalization error (GE) of machine learning models is fundamental, with resampling methods being the most common approach. However, in non-standard settings, parti…
Causal Fair Machine Learning via Rank-Preserving Interventional Distributions
Ludwig Bothmann, Susanne Dandl, Michael Schomaker
A decision can be defined as fair if equal individuals are treated equally and unequals unequally. Adopting this definition, the task of designing machine learning (ML) models that…
Interpretable Regional Descriptors: Hyperbox-Based Local Explanations
Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl +1
This work introduces interpretable regional descriptors, or IRDs, for local, model-agnostic interpretations. IRDs are hyperboxes that describe how an observation's feature values c…