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.
| Version: | 1.1.1 |
| Depends: | R (≥ 4.1) |
| Imports: | butcher (≥ 0.1.3),cli,dplyr (≥ 1.1.0),foreach,furrr,future,generics,ggplot2,glmnet,glue,parsnip (≥ 1.2.0),purrr (≥ 1.0.0),recipes (≥ 1.0.10),rlang (≥ 1.1.0),rsample (≥ 1.2.0), stats,tibble (≥ 2.1.3),tidyr,tune (≥1.2.0),vctrs (≥ 0.6.1),workflows (≥ 1.1.4) |
| Suggests: | covr,h2o,kernlab,kknn,knitr,modeldata,nnet,ranger,rmarkdown,testthat (≥ 3.0.0),workflowsets (≥ 0.1.0),yardstick (≥ 1.1.0) |
| Published: | 2025-05-27 |
| DOI: | 10.32614/CRAN.package.stacks |
| Author: | Simon Couch [aut, cre], Max Kuhn [aut], Posit Software, PBC [cph, fnd] |
| Maintainer: | Simon Couch <simon.couch at posit.co> |
| BugReports: | https://github.com/tidymodels/stacks/issues |
| License: | MIT + fileLICENSE |
| URL: | https://stacks.tidymodels.org/,https://github.com/tidymodels/stacks |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | stacks results |