Title: Extra Recipes for Encoding Categorical Predictors
Description: Factor predictors can be converted to one or more numeric representations using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737>. All encoding methods are supervised.
Imports: rstanarm, keras, stats, dplyr, purrr, rlang, utils, broom,

Imports: rstanarm, keras, stats, dplyr, purrr, rlang, utils, generics,

Description: Predictors can be converted to one or more numeric representations using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737>. All encoding methods are supervised.
tidyr, tibble, lme4, tensorflow, uwot, withr
Suggests: testthat, knitr, rmarkdown, covr, ggplot2

person(given = "Max",    family = "Kuhn",    email = "max@rstudio.com",    role = c("aut", "cre")),
tidyr (>= 0.8.3), tibble, lme4, tensorflow, uwot, withr

Suggests: testthat, knitr, rmarkdown, covr, ggplot2, modeldata

Description: Predictors can be converted to one or more numeric representations using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737>. Most encoding methods are supervised.
tidyr, tibble, lme4, tensorflow, uwot, withr, rsample
Suggests: testthat, knitr, rmarkdown, covr, ggplot2, modeldata, rpart,

Imports: rstanarm, keras, stats, dplyr, purrr, rlang, utils, generics
(>= 0.1.0), tidyr, tibble, lme4, tensorflow, uwot, withr,

Imports: keras, stats, dplyr, purrr, rlang, utils, generics (>= 0.1.0),
tidyr, tibble, tensorflow, uwot, withr, rsample
Suggests: rstanarm, lme4, testthat, knitr, rmarkdown, covr, ggplot2,

Title: Extra Recipes for Encoding Predictors
Description: Predictors can be converted to one or more numeric
representations using a variety of methods. Effect encodings using
simple generalized linear models <arXiv:1611.09477> or nonlinear
models <arXiv:1604.06737> can be used.  There are also functions for
dimension reduction and other approaches.
Imports: dplyr, generics (>= 0.1.0), keras, lifecycle, purrr, rlang (>=
0.4.10), rsample, stats, tensorflow, tibble, tidyr, utils,
Suggests: covr, ggplot2, irlba, knitr, lme4, modeldata, rmarkdown,
rpart, rstanarm, testthat (>= 3.0.0), VBsparsePCA, xgboost