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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: | 1.0.5 |
| Depends: | R (≥ 3.6) |
| Imports: | butcher (≥ 0.1.3), cli, doFuture, dplyr (≥ 1.1.0), foreach, future, generics, ggplot2, glmnet, glue, parsnip (≥ 1.2.0), purrr (≥ 1.0.0), recipes (≥ 1.0.10), rlang (≥ 1.1.3), 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, mockr, modeldata, nnet, ranger, rmarkdown, testthat (≥ 3.0.0), workflowsets (≥ 0.1.0), yardstick (≥ 1.1.0) |
| Published: | 2024-07-22 |
| 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 + 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_1.0.5.tar.gz |
| Windows binaries: | r-devel: stacks_1.0.5.zip, r-release: stacks_1.0.5.zip, r-oldrel: stacks_1.0.5.zip |
| macOS binaries: | r-release (arm64): stacks_1.0.5.tgz, r-oldrel (arm64): stacks_1.0.5.tgz, r-release (x86_64): stacks_1.0.5.tgz, r-oldrel (x86_64): stacks_1.0.5.tgz |
| Old sources: | stacks archive |
| Reverse suggests: | bundle, DALEXtra, tidysdm, vetiver |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.