22 citations · 51 across the 11 of their papers we have counts for
3 papers · 1 filter
A Central Limit Theorem for the permutation importance measure
Nico Föge, Lena Schmid, Marc Ditzhaus +1
Random Forests have become a widely used tool in machine learning since their introduction in 2001, known for their strong performance in classification and regression tasks. One k…
TREE: Tree Regularization for Efficient Execution
Lena Schmid, Daniel Biebert, Christian Hakert +4
The rise of machine learning methods on heavily resource constrained devices requires not only the choice of a suitable model architecture for the target platform, but also the opt…
Even naive trees are consistent
Nico Föge, Markus Pauly, Lena Schmid +1
The last decade has shed some light on theoretical properties such as their consistency for regression tasks. In the current paper, we propose a new class of very simple learners b…