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Books and Theses
- 2019
[b1]Philipp Probst:
Hyperparameters, tuning and meta-learning for random forest and other machine learning algorithms. Ludwig Maximilian University of Munich, Germany, 2019
Journal Articles
- 2021
- [j6]Moritz Herrmann
, Philipp Probst, Roman Hornung, Vindi Jurinovic, Anne-Laure Boulesteix:
Large-scale benchmark study of survival prediction methods using multi-omics data. Briefings Bioinform. 22(3) (2021) - 2019
- [j5]Philipp Probst, Anne-Laure Boulesteix, Bernd Bischl:
Tunability: Importance of Hyperparameters of Machine Learning Algorithms. J. Mach. Learn. Res. 20: 53:1-53:32 (2019) - [j4]Philipp Probst, Marvin N. Wright, Anne-Laure Boulesteix:
Hyperparameters and tuning strategies for random forest. WIREs Data Mining Knowl. Discov. 9(3) (2019) - 2018
- [j3]Raphaël Couronné, Philipp Probst, Anne-Laure Boulesteix:
Random forest versus logistic regression: a large-scale benchmark experiment. BMC Bioinform. 19(1): 270:1-270:14 (2018) - 2017
- [j2]Philipp Probst, Anne-Laure Boulesteix:
To Tune or Not to Tune the Number of Trees in Random Forest. J. Mach. Learn. Res. 18: 181:1-181:18 (2017) - [j1]Philipp Probst, Quay Au, Giuseppe Casalicchio, Clemens Stachl, Bernd Bischl:
Multilabel Classification with R Package mlr. R J. 9(1): 352 (2017)
Conference and Workshop Papers
- 2021
- [c2]Florian Pfisterer, Jan N. van Rijn, Philipp Probst, Andreas C. Müller, Bernd Bischl:
Learning multiple defaults for machine learning algorithms. GECCO Companion 2021: 241-242 - 2012
- [c1]Florian Michahelles, Philipp Probst:
Object circles: modeling physical objects as social relationships. MUM 2012: 23
Informal and Other Publications
- 2020
- [i6]Moritz Herrmann, Philipp Probst, Roman Hornung, Vindi Jurinovic, Anne-Laure Boulesteix:
Large-scale benchmark study of survival prediction methods using multi-omics data. CoRR abs/2003.03621 (2020) - 2018
- [i5]Philipp Probst, Marvin N. Wright, Anne-Laure Boulesteix:
Hyperparameters and Tuning Strategies for Random Forest. CoRR abs/1804.03515 (2018) - [i4]Daniel Kühn, Philipp Probst, Janek Thomas, Bernd Bischl:
Automatic Exploration of Machine Learning Experiments on OpenML. CoRR abs/1806.10961 (2018) - [i3]Florian Pfisterer, Jan N. van Rijn, Philipp Probst, Andreas C. Müller, Bernd Bischl:
Learning Multiple Defaults for Machine Learning Algorithms. CoRR abs/1811.09409 (2018) - 2017
- [i2]Philipp Probst, Anne-Laure Boulesteix:
To tune or not to tune the number of trees in random forest? CoRR abs/1705.05654 (2017) - 2016
- [i1]Julia Schiffner, Bernd Bischl, Michel Lang, Jakob Richter, Zachary M. Jones, Philipp Probst, Florian Pfisterer, Mason Gallo, Dominik Kirchhoff, Tobias Kühn, Janek Thomas, Lars Kotthoff:
mlr Tutorial. CoRR abs/1609.06146 (2016)
Coauthor Index
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