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: | 0.2.2 |
| Depends: | R (≥ 2.10) |
| Imports: | tune (≥ 0.1.3), dplyr (≥ 1.0.0), rlang (≥ 0.4.0), tibble (≥ 2.1.3), purrr (≥ 0.3.2), parsnip (≥ 0.0.4), workflows (≥ 0.2.2), recipes (≥ 0.1.15), rsample (≥ 0.1.1), workflowsets (≥ 0.1.0), butcher (≥ 0.1.3), yardstick, tidyr, dials, glue, ggplot2, glmnet, cli, stats, foreach, generics |
| Suggests: | testthat, covr, kernlab, knitr, modeldata, rmarkdown, ranger, nnet, kknn |
| Published: | 2022-01-06 |
| Author: | Simon Couch [aut, cre], Max Kuhn [aut], RStudio [cph] |
| Maintainer: | Simon Couch <simonpatrickcouch at gmail.com> |
| BugReports: | https://github.com/tidymodels/stacks/issues |
| License: | MIT + file LICENSE |
| URL: | https://stacks.tidymodels.org/, https://github.com/tidymodels/stacks |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | stacks results |
| Reference manual: | stacks.pdf |
| Vignettes: |
Getting Started With stacks Classification Models With stacks |
| Package source: | stacks_0.2.2.tar.gz |
| Windows binaries: | r-devel: stacks_0.2.2.zip, r-release: stacks_0.2.2.zip, r-oldrel: stacks_0.2.2.zip |
| macOS binaries: | r-release (arm64): stacks_0.2.2.tgz, r-release (x86_64): stacks_0.2.2.tgz, r-oldrel: stacks_0.2.2.tgz |
| Old sources: | stacks archive |
Please use the canonical form https://CRAN.R-project.org/package=stacks to link to this page.