1.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Ludwig-Maximilians-Universität MünchenDE63 papers
- Technical University of MunichDE41 papers
- LMU KlinikumDE29 papers
- Imperial College LondonGB8 papers
- Helmholtz MunichDE6 papers
- TUM KlinikumDE6 papers
- Zimmer Biomet (Germany)DE6 papers
- Fraunhofer Institute for Integrated CircuitsDE4 papers
- Munich School of PhilosophyDE4 papers
- TU Dortmund UniversityDE4 papers
- University College LondonGB4 papers
- Zimmer Biomet (Netherlands)NL4 papers
3 papers · 2 filters
Multi forests: Variable importance for multi-class outcomes
Roman Hornung, Alexander Hapfelmeier
In prediction tasks with multi-class outcomes, identifying covariates specifically associated with one or more outcome classes can be important. Conventional variable importance me…
Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects
David Köhler, David Rügamer, Matthias Schmid
Machine learning (ML) has seen significant growth in both popularity and importance. The high prediction accuracy of ML models is often achieved through complex black-box architect…
A Guide to Feature Importance Methods for Scientific Inference
Fiona Katharina Ewald, Ludwig Bothmann, Marvin N. Wright +3
While machine learning (ML) models are increasingly used due to their high predictive power, their use in understanding the data-generating process (DGP) is limited. Understanding…