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Markus Loecher
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2020 – today
- 2025
- [j2]Bastian Pfeifer, Arne Gevaert, Markus Loecher, Andreas Holzinger:
Tree smoothing: Post-hoc regularization of tree ensembles for interpretable machine learning. Inf. Sci. 690: 121564 (2025) - 2022
- [c3]Markus Loecher, Dingyi Lai, Wu Qi:
Approximation of SHAP Values for Randomized Tree Ensembles. CD-MAKE 2022: 19-30 - [c2]Markus Loecher:
Debiasing MDI Feature Importance and SHAP Values in Tree Ensembles. CD-MAKE 2022: 114-129 - [c1]Raphael Baudeu, Marvin N. Wright, Markus Loecher:
Are SHAP Values Biased Towards High-Entropy Features? PKDD/ECML Workshops (1) 2022: 418-433 - 2021
- [j1]Markus Loecher:
The Perils of Misspecified Priors and Optional Stopping in Multi-Armed Bandits. Frontiers Artif. Intell. 4: 715690 (2021) - [i3]Markus Loecher, Qi Wu:
Data-driven advice for interpreting local and global model predictions in bioinformatics problems. CoRR abs/2108.06201 (2021) - 2020
- [i2]Markus Loecher:
Unbiased variable importance for random forests. CoRR abs/2003.02106 (2020) - [i1]Markus Loecher:
From unbiased MDI Feature Importance to Explainable AI for Trees. CoRR abs/2003.12043 (2020)
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