Predictors can be converted to one or more numeric
representations using a variety of methods. Effect encodings using
simple generalized linear models <doi:10.48550/arXiv.1611.09477> or nonlinear
models <doi:10.48550/arXiv.1604.06737> can be used. There are also functions for
dimension reduction and other approaches.
| Version: |
1.1.4 |
| Depends: |
R (≥ 3.6), recipes (≥ 1.0.7) |
| Imports: |
glue, dplyr (≥ 1.1.0), generics (≥ 0.1.0), lifecycle, purrr, rlang (≥ 0.4.10), rsample, stats, tibble, tidyr, utils, uwot, withr, vctrs |
| Suggests: |
covr, dials (≥ 1.2.0), ggplot2, hardhat, irlba, keras, knitr, lme4, modeldata, rmarkdown, rpart, rstanarm, stringdist, tensorflow, testthat (≥ 3.0.0), VBsparsePCA, xgboost |
| Published: |
2024-03-20 |
| Author: |
Emil Hvitfeldt 
[aut, cre],
Max Kuhn [aut],
Posit Software, PBC [cph, fnd] |
| Maintainer: |
Emil Hvitfeldt <emil.hvitfeldt at posit.co> |
| BugReports: |
https://github.com/tidymodels/embed/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://embed.tidymodels.org, https://github.com/tidymodels/embed |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
embed results |