28 citations · 33 across the 2 of their papers we have counts for
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cs.LG2019
Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations
Christian A. Scholbeck, Christoph Molnar, Christian Heumann +2
Model-agnostic interpretation techniques allow us to explain the behavior of any predictive model. Due to different notations and terminology, it is difficult to see how they are r…
stat.ML2019
Quantifying Model Complexity via Functional Decomposition for Better Post-Hoc Interpretability
Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
Post-hoc model-agnostic interpretation methods such as partial dependence plots can be employed to interpret complex machine learning models. While these interpretation methods can…