1 code implementation • 20 Dec 2023 • Hannah Blocher, Georg Schollmeyer, Malte Nalenz, Christoph Jansen
We propose a framework for descriptively analyzing sets of partial orders based on the concept of depth functions.
no code implementations • 23 Oct 2023 • Roman Hornung, Malte Nalenz, Lennart Schneider, Andreas Bender, Ludwig Bothmann, Bernd Bischl, Thomas Augustin, Anne-Laure Boulesteix
Our findings corroborate the concern that standard resampling methods often yield biased GE estimates in non-standard settings, underscoring the importance of tailored GE estimation.
1 code implementation • 19 Apr 2023 • Hannah Blocher, Georg Schollmeyer, Christoph Jansen, Malte Nalenz
We propose a framework for descriptively analyzing sets of partial orders based on the concept of depth functions.
no code implementations • 5 Sep 2022 • Christoph Jansen, Malte Nalenz, Georg Schollmeyer, Thomas Augustin
This yields indeed a powerful framework for the statistical comparison of classifiers over multiple data sets with respect to multiple quality criteria simultaneously.
no code implementations • 16 Feb 2017 • Malte Nalenz, Mattias Villani
The aggressive noise shrinkage of our prior also makes it possible to complement the rules from boosting in Friedman and Popescu (2008) with an additional set of trees from random forest, which brings a desirable diversity to the ensemble.