Markus Loecher

According to our database, Markus Loecher authored at least 9 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests.

Kristin Blesch, Niklas Koenen, Jan Kapar, Pegah Golchian, Lukas Burk, Markus Loecher, Marvin N. Wright

CoRR, January, 2025

Tree smoothing: Post-hoc regularization of tree ensembles for interpretable machine learning.

Bastian Pfeifer, Arne Gevaert, Markus Loecher, Andreas Holzinger

Inf. Sci., 2025

2022

Are SHAP Values Biased Towards High-Entropy Features?

Raphael Baudeu, Marvin N. Wright, Markus Loecher

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022

Approximation of SHAP Values for Randomized Tree Ensembles.

Markus Loecher, Dingyi Lai, Wu Qi

Proceedings of the Machine Learning and Knowledge Extraction, 2022

Debiasing MDI Feature Importance and SHAP Values in Tree Ensembles.

Markus Loecher

Proceedings of the Machine Learning and Knowledge Extraction, 2022

2021

The Perils of Misspecified Priors and Optional Stopping in Multi-Armed Bandits.

Markus Loecher

Frontiers Artif. Intell., 2021

Data-driven advice for interpreting local and global model predictions in bioinformatics problems.

Markus Loecher, Qi Wu

CoRR, 2021

2020

From unbiased MDI Feature Importance to Explainable AI for Trees.

Markus Loecher

CoRR, 2020

Unbiased variable importance for random forests.

Markus Loecher

CoRR, 2020