Thesis/Theses examined by Bischl, Bernd

Scholbeck, Christian Alexander (2024): Bridging gaps in interpretable machine learning: sensitivity analysis, marginal effects, and cluster explanations. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Probst, Philipp (2019): Hyperparameters, tuning and meta-learning for random forest and other machine learning algorithms. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics