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Characterizing model uncertainty in ensemble learning. towards more robust representation and learning of tree ensemble methods
Characterizing model uncertainty in ensemble learning. towards more robust representation and learning of tree ensemble methods
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Machine Learning, Interpretability, Ensemble Learning, Uncertainty Quantification
Nalenz, Malte
2022
English
Universitätsbibliothek der Ludwig-Maximilians-Universität München
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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