Showing stat.MLShow all
2 papers · 1 filter
stat.ML2020
Random boosting and random^2 forests -- A random tree depth injection approach
Tobias Markus Krabel, Thi Ngoc Tien Tran, Andreas Groll +2
The induction of additional randomness in parallel and sequential ensemble methods has proven to be worthwhile in many aspects. In this manuscript, we propose and examine a novel r…
stat.ML2016
Fast model selection by limiting SVM training times
Aydin Demircioglu, Daniel Horn, Tobias Glasmachers +2
Kernelized Support Vector Machines (SVMs) are among the best performing supervised learning methods. But for optimal predictive performance, time-consuming parameter tuning is cruc…