4 papers
Large-scale benchmark study of survival prediction methods using multi-omics data
Moritz Herrmann, Philipp Probst, Roman Hornung +2
Multi-omics data, that is, datasets containing different types of high-dimensional molecular variables (often in addition to classical clinical variables), are increasingly generat…
Essential guidelines for computational method benchmarking
Lukas M. Weber, Wouter Saelens, Robrecht Cannoodt +6
In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies…
Hyperparameters and Tuning Strategies for Random Forest
Philipp Probst, Marvin Wright, Anne-Laure Boulesteix
The random forest algorithm (RF) has several hyperparameters that have to be set by the user, e.g., the number of observations drawn randomly for each tree and whether they are dra…
Tunability: Importance of Hyperparameters of Machine Learning Algorithms
Philipp Probst, Bernd Bischl, Anne-Laure Boulesteix
Modern supervised machine learning algorithms involve hyperparameters that have to be set before running them. Options for setting hyperparameters are default values from the softw…