| Nalenz, Malte (2022): Characterizing model uncertainty in ensemble learning: towards more robust representation and learning of tree ensemble methods. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics |
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Nalenz_Malte.pdf 3MB |
DOI: 10.5282/edoc.30379
| Item Type: | Theses (Dissertation, LMU Munich) |
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| Keywords: | Machine Learning, Interpretability, Ensemble Learning, Uncertainty Quantification |
| Subjects: | 000 Computers, Information and General Reference 000 Computers, Information and General Reference > 004 Data processing computer science 500 Natural sciences and mathematics |
| Faculties: | Faculty of Mathematics, Computer Science and Statistics |
| Language: | English |
| Date of oral examination: | 5. May 2022 |
| 1. Referee: | Augustin, Thomas |
| MD5 Checksum of the PDF-file: | 1e8e566f2d9d4894566e8d797654a2fd |
| Signature of the printed copy: | 0001/UMC 29040 |
| ID Code: | 30379 |
| Deposited On: | 14. Sep 2022 09:35 |
| Last Modified: | 14. Sep 2022 09:35 |
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