Papers

2021

Molnar, Christoph, et al.
“Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process.”
arXiv preprint arXiv:2109.01433 (2021). [pdf]

König, Gunnar, et al.
“Relative feature importance.”
2020 25th International Conference on Pattern Recognition (ICPR). IEEE, 2021. [pdf]

König, Gunnar, Timo Freiesleben, and Moritz Grosse-Wentrup.
“A causal perspective on meaningful and robust algorithmic recourse.”
arXiv preprint arXiv:2107.07853 (2021). [pdf]

König, Gunnar, et al.
“Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT).”
arXiv preprint arXiv:2106.08086 (2021). [pdf]

2020

Molnar, Christoph, et al.
“Model-agnostic Feature Importance and Effects with Dependent Features–A Conditional Subgroup Approach.”
arXiv preprint arXiv:2006.04628 (2020). [pdf]

Molnar, Christoph, et al.
“General pitfalls of model-agnostic interpretation methods for machine learning models.”
arXiv preprint arXiv:2007.04131 (2020). [pdf]