Optimally Weighted Ensembles of Regression Models: Exact Weight Optimization and Applications. (arXiv:2206.11263v1 [cs.LG])

Web: http://arxiv.org/abs/2206.11263

Automated model selection is often proposed to users to choose which machine
learning model (or method) to apply to a given regression task. In this paper,
we show that combining different regression models can yield better results
than selecting a single ('best') regression model, and outline an efficient
method that obtains optimally weighted convex linear combination from a
heterogeneous set of regression models. More specifically, in this paper, a
heuristic weight optimization, used in a preceding conference paper, is
replaced …

applications arxiv lg models optimization regression