Model stacking is an ensemble technique that involves training a model to combine the outputs of many diverse statistical models, and has been shown to improve predictive performance in a variety of settings. 'stacks' implements a grammar for 'tidymodels'-aligned model stacking.
Author
Maintainer: Simon Couch simon.couch@posit.co
Authors:
Max Kuhn max@posit.co
Other contributors:
Posit Software, PBC [copyright holder, funder]