Merge pull request #241 from tidymodels/RC-1.1.5

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: embed
 Title: Extra Recipes for Encoding Predictors
-Version: 1.1.4.9000
+Version: 1.1.5.9000
 Authors@R: c(
     person("Emil", "Hvitfeldt", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0002-0679-1945")),
@@ -10,15 +10,15 @@ Authors@R: c(
   )
 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.
+    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.
 License: MIT + file LICENSE
 URL: https://embed.tidymodels.org, https://github.com/tidymodels/embed
 BugReports: https://github.com/tidymodels/embed/issues
 Depends: 
     R (>= 3.6),
-    recipes (>= 1.1.0.9000)
+    recipes (>= 1.1.0)
 Imports:
     cli,
     glue,
@@ -53,8 +53,6 @@ Suggests:
     testthat (>= 3.0.0),
     VBsparsePCA,
     xgboost
-Remotes:
-    tidymodels/recipes
 ByteCompile: true
 Config/Needs/website: tidymodels, ggiraph, tidyverse/tidytemplate, reticulate
 Config/testthat/edition: 3

NEWS.md

@@ -1,6 +1,12 @@
 # embed (development version)
 
-* `step_umap()` has tunable `initial` and `target_weight` arguments. [#223](https://github.com/tidymodels/embed/issues/223), [#222](https://github.com/tidymodels/embed/issues/222))
+# embed 1.1.5
+
+## Improvements
+
+* `step_umap()` has tunable `initial` and `target_weight` arguments. (#223, #222)
+
+* All messages, warnings and errors has been translated to use {cli} package (#153, #155).
 
 # embed 1.1.4
 

R/collapse_cart.R

@@ -6,7 +6,7 @@
 #' @param recipe A recipe object. The step will be added to the sequence of
 #'   operations for this recipe.
 #' @param ... One or more selector functions to choose which variables are
-#'   affected by the step. See [selections()] for more details. For the `tidy`
+#'   affected by the step. See [recipes::selections] for more details. For the `tidy`
 #'   method, these are not currently used.
 #' @param outcome A call to `vars` to specify which variable is used as the
 #'   outcome to train CART models in order to pool factor levels.
@@ -21,7 +21,7 @@
 #'   complex trees.
 #' @param results A list of results to convert to new factor levels.
 #' @param skip A logical. Should the step be skipped when the recipe is baked by
-#'   [bake()]? While all operations are baked when [prep()] is run, some
+#'   [recipes::bake]? While all operations are baked when [recipes::prep] is run, some
 #'   operations may not be able to be conducted on new data (e.g. processing the
 #'   outcome variable(s)). Care should be taken when using `skip = TRUE` as it
 #'   may affect the computations for subsequent operations
@@ -42,7 +42,7 @@
 #'
 #' # Tidying
 #' 
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `terms`, `old`, `new`, and `id`:
 #' 
 #' \describe{

R/collapse_stringdist.R

@@ -5,7 +5,7 @@
 #'
 #' @inheritParams recipes::step_center
 #' @param ... One or more selector functions to choose which variables are
-#'   affected by the step. See [selections()] for more details.  For the `tidy`
+#'   affected by the step. See [recipes::selections] for more details.  For the `tidy`
 #'   method, these are not currently used.
 #' @param role Not used by this step since no new variables are created.
 #' @param distance Integer, value to determine which strings should be collapsed
@@ -17,7 +17,7 @@
 #'   [stringdist::stringdistmatrix()] such as `weight`, `q`, `p`, and `bt`, that
 #'   are used for different values of `method`. 
 #' @param results A list denoting the way the labels should be collapses is
-#'   stored here once this preprocessing step has be trained by [prep()].
+#'   stored here once this preprocessing step has be trained by [recipes::prep].
 #' @param columns A character string of variable names that will be populated
 #'   (eventually) by the `terms` argument.
 #' @return An updated version of `recipe` with the new step added to the
@@ -28,7 +28,7 @@
 #'
 #' # Tidying
 #' 
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `terms`, `from`, `to`, and `id`:
 #' 
 #' \describe{

R/discretize_cart.R

@@ -7,7 +7,7 @@
 #' @param recipe A recipe object. The step will be added to the sequence of
 #'   operations for this recipe.
 #' @param ... One or more selector functions to choose which variables are
-#'   affected by the step. See [selections()] for more details.
+#'   affected by the step. See [recipes::selections] for more details.
 #' @param role Defaults to `"predictor"`.
 #' @param trained A logical to indicate if the quantities for preprocessing have
 #'   been estimated.
@@ -46,7 +46,7 @@
 #'
 #' # Tidying
 #' 
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `terms`, `value`, and `id`:
 #' 
 #' \describe{

R/discretize_xgb.R

@@ -7,7 +7,7 @@
 #' @param recipe A recipe object. The step will be added to the sequence of
 #'   operations for this recipe.
 #' @param ... One or more selector functions to choose which variables are
-#'   affected by the step. See [selections()] for more details.
+#'   affected by the step. See [recipes::selections] for more details.
 #' @param role Defaults to `"predictor"`.
 #' @param trained A logical to indicate if the quantities for preprocessing have
 #'   been estimated.
@@ -63,7 +63,7 @@
 #'
 #' # Tidying
 #' 
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `terms`, `value`, and `id`:
 #' 
 #' \describe{

R/embed.R

@@ -103,7 +103,7 @@
 #'
 #' # Tidying
 #' 
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' a number of columns with embedding information, and columns `terms`, 
 #' `levels`, and `id`:
 #' 

R/feature_hash.R

@@ -35,7 +35,7 @@
 #'
 #' # Tidying
 #' 
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `terms` and `id`:
 #' 
 #' \describe{

R/lencode_bayes.R

@@ -61,7 +61,7 @@
 #'
 #' # Tidying
 #'
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `level`, `value`, `terms`, and `id`:
 #' 
 #' \describe{

R/lencode_glm.R

@@ -44,7 +44,7 @@
 #'
 #' # Tidying
 #'
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `level`, `value`, `terms`, and `id`:
 #' 
 #' \describe{

R/lencode_mixed.R

@@ -57,7 +57,7 @@
 #'
 #' # Tidying
 #'
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `level`, `value`, `terms`, and `id`:
 #' 
 #' \describe{

R/pca_sparse.R

@@ -8,7 +8,7 @@
 #' @inheritParams recipes::step_pca
 #' @inherit step_lencode_bayes return
 #' @param ... One or more selector functions to choose which variables will be
-#'   used to compute the components. See [selections()] for more details. For
+#'   used to compute the components. See [recipes::selections] for more details. For
 #'   the `tidy` method, these are not currently used.
 #' @param role For model terms created by this step, what analysis role should
 #'   they be assigned? By default, the function assumes that the new principal
@@ -20,7 +20,7 @@
 #'   output. Defaults to `FALSE`.
 #' @param options A list of options to the default method for [irlba::ssvd()].
 #' @param res The rotation matrix once this preprocessing step has be trained by
-#'   [prep()].
+#'   [recipes::prep].
 #' @param prefix A character string that will be the prefix to the resulting new
 #'   variables. See notes below.
 #' @return An updated version of `recipe` with the new step added to the
@@ -46,7 +46,7 @@
 #'
 #' # Tidying
 #'
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `terms`, `value`, `component`, and `id`:
 #'
 #' \describe{

R/pca_sparse_bayes.R

@@ -8,7 +8,7 @@
 #' @inheritParams recipes::step_pca
 #' @inherit step_lencode_bayes return
 #' @param ... One or more selector functions to choose which variables will be
-#'   used to compute the components. See [selections()] for more details. For
+#'   used to compute the components. See [recipes::selections] for more details. For
 #'   the `tidy` method, these are not currently used.
 #' @param role For model terms created by this step, what analysis role should
 #'   they be assigned? By default, the function assumes that the new principal
@@ -25,7 +25,7 @@
 #' @param options A list of options to the default method for
 #'   [VBsparsePCA::VBsparsePCA()].
 #' @param res The rotation matrix once this preprocessing step has been trained
-#'   by [prep()].
+#'   by [recipes::prep].
 #' @param prefix A character string that will be the prefix to the resulting new
 #'   variables. See notes below.
 #' @return An updated version of `recipe` with the new step added to the
@@ -65,7 +65,7 @@
 #'
 #' # Tidying
 #'
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `terms`, `value`, `component`, and `id`:
 #'
 #' \describe{

R/pca_truncated.R

@@ -11,7 +11,7 @@
 #'   `center = FALSE`, `scale. = FALSE`, and `tol = NULL`. **Note** that the
 #'   argument `x` should not be passed here (or at all).
 #' @param res The [irlba::prcomp_irlba()] object is stored here once this
-#'   preprocessing step has be trained by [prep()].
+#'   preprocessing step has be trained by [recipes::prep].
 #' @template step-return
 #' @details
 #'
@@ -24,8 +24,8 @@
 #'
 #' It is advisable to standardize the variables prior to running PCA. Here, each
 #' variable will be centered and scaled prior to the PCA calculation. This can
-#' be changed using the `options` argument or by using [step_center()] and
-#' [step_scale()].
+#' be changed using the `options` argument or by using [recipes::step_center()] and
+#' [recipes::step_scale()].
 #'
 #' ```{r, echo = FALSE, results="asis"}
 #' prefix <- "PC"
@@ -35,7 +35,7 @@
 #' 
 #' # Tidying
 #'
-#' When you [`tidy()`][tidy.recipe()] this step two things can happen depending
+#' When you [`tidy()`][recipes::tidy.recipe] this step two things can happen depending
 #' the `type` argument. If `type = "coef"` a tibble returned with 4 columns
 #' `terms`, `value`, `component` , and `id`:
 #'

R/umap.R

@@ -34,8 +34,8 @@
 #'   `n_threads` are set.
 #' @param seed Two integers to control the random numbers used by the numerical
 #'   methods. The default pulls from the main session's stream of numbers and
-#'   will give reproducible results if the seed is set prior to calling [prep()]
-#'   or [bake()].
+#'   will give reproducible results if the seed is set prior to calling [recipes::prep]
+#'   or [recipes::bake].
 #' @param retain Use `keep_original_cols` instead to specify whether the
 #'   original predictors should be retained along with the new embedding
 #'   variables.
@@ -57,7 +57,7 @@
 #'
 #' # Tidying
 #'
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #'  columns `terms` and `id`:
 #' 
 #' \describe{

R/woe.R

@@ -8,7 +8,7 @@
 #' @inheritParams recipes::step_pca
 #' @inherit step_center return
 #' @param ... One or more selector functions to choose which variables will be
-#'   used to compute the components. See [selections()] for more details. For
+#'   used to compute the components. See [recipes::selections] for more details. For
 #'   the `tidy` method, these are not currently used.
 #' @param role For model terms created by this step, what analysis role should
 #'   they be assigned?. By default, the function assumes that the new woe
@@ -45,7 +45,7 @@
 #' with a binary outcome.  To apply it on numerical predictors, it is advisable
 #' to discretize the variables prior to running WoE. Here, each variable will be
 #' binarized to have woe associated later. This can achieved by using
-#' [step_discretize()].
+#' [recipes::step_discretize()].
 #'
 #' The argument `Laplace` is an small quantity added to the proportions of 1's
 #' and 0's with the goal to avoid log(p/0) or log(0/p) results. The numerical
@@ -62,12 +62,12 @@
 #'
 #' # Tidying
 #'
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble with columns `terms`
 #' (the selectors or variables selected), `value`, `n_tot`, `n_bad`, `n_good`,
 #' `p_bad`, `p_good`, `woe` and `outcome` is returned.. See [dictionary()] for
 #' more information.
 #' 
-#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
+#' When you [`tidy()`][recipes::tidy.recipe] this step, a tibble is returned with
 #' columns `terms` `value`, `n_tot`, `n_bad`, `n_good`, `p_bad`, `p_good`, `woe`
 #' and `outcome` and `id`:
 #' 

README.Rmd

@@ -82,7 +82,7 @@ pak::pak("tidymodels/embed")
 
 This project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.
 
-- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on RStudio Community](https://community.rstudio.com/new-topic?category_id=15&tags=tidymodels,question).
+- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on RStudio Community](https://forum.posit.co/new-topic?category_id=15&tags=tidymodels,question).
 
 - If you think you have encountered a bug, please [submit an issue](https://github.com/tidymodels/embed/issues).