Feb 24, 2024 · Feb 24, 2024
diff --git a/NEWS.md b/NEWS.md

 * `step_umap()` has gained `initial` and `target_weight` arguments. (#213)

 * Calling `?tidy.step_*()` now sends you to the documentation for `step_*()` where the outcome is documented. (#216)

 * Documentation for tidy methods for all steps has been improved to describe the return value more accurately. (#217)

 # embed 1.1.3

 * `step_collapse_stringdist()` will now return predictors as factors. (#204)

 * Fixed regression from 1.1.2 in `step_lencode_glm()` where it couldn't be used on multiple columns.

 * Calling `?tidy.step_*()` now sends you to the documentation for `step_*()` where the outcome is documented. (#216)

 # embed 1.1.2

 ## Improvements
diff --git a/R/collapse_cart.R b/R/collapse_cart.R
 #' find any signal in the data.
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `"terms"`
 #' (the column being modified), `"old"` (the old levels), `"new"` (the new
 #' levels), and `"id"`. If the CART model failed or could not find a good split,
 #' the requested predictor will not be in the results.
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' columns `terms`, `old`, `new`, and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{old}{character, the old levels}
 #'   \item{new}{character, the new levels}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' @template case-weights-not-supported
 #'
diff --git a/R/collapse_stringdist.R b/R/collapse_stringdist.R
 #' @details
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `"terms"`
 #' (the column being modified), `"from"` (the old levels), `"to"` (the new
 #' levels), and `"id"`.
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' columns `terms`, `from`, `to`, and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{from}{character, the old levels}
 #'   \item{too}{character, the new levels}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' @template case-weights-not-supported
 #'
diff --git a/R/discretize_cart.R b/R/discretize_cart.R
 #' Note that the original data will be replaced with the new bins.
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
 #' (the columns that is selected), `values` is returned.
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' columns `terms`, `value`, and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{value}{numeric, location of the splits}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' ```{r, echo = FALSE, results="asis"}
 #' step <- "step_discretize_cart"
diff --git a/R/discretize_xgb.R b/R/discretize_xgb.R
 #' Note that the original data will be replaced with the new bins.
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
 #' (the columns that is selected), `values` is returned.
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' columns `terms`, `value`, and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{value}{numeric, location of the splits}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' ```{r, echo = FALSE, results="asis"}
 #' step <- "step_discretize_xgb"
diff --git a/R/embed.R b/R/embed.R
 #' this step with `caret`, avoid parallel processing.
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
 #' (the selectors or variables selected), `levels` (levels in variable), and a
 #' number of columns with embedding information are returned.
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' a number of columns with embedding information, and columns `terms`,
 #' `levels`, and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{levels}{character, levels in variable}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' ```{r, echo = FALSE, results="asis"}
 #' step <- "step_embed"
diff --git a/R/feature_hash.R b/R/feature_hash.R
 #' [recipes::step_zv()]) is recommended for any recipe that uses hashed columns.
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
 #' (the columns that is selected)  is returned.
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' columns `terms` and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' @template case-weights-not-supported
 #'
diff --git a/R/lencode_bayes.R b/R/lencode_bayes.R
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
 #' (the selectors or variables selected), `value` and `component` is returned.
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' columns `level`, `value`, `terms`, and `id`:
 #'
 #' \describe{
 #'   \item{level}{character, the factor levels}
 #'   \item{value}{numeric, the encoding}
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' @template case-weights-supervised
 #'
 #' @references
 #' "Hierarchical Partial Pooling for Repeated Binary Trials"
 #' \url{https://tinyurl.com/stan-pooling}
 #'
 #' "Prior Distributions for `rstanarm`` Models"
 #' "Prior Distributions for `rstanarm` Models"
 #' \url{https://tinyurl.com/stan-priors}
 #'
 #' "Estimating Generalized (Non-)Linear Models with Group-Specific Terms with
diff --git a/R/lencode_glm.R b/R/lencode_glm.R
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
 #' (the selectors or variables selected), `value` and `component` is returned.
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' columns `level`, `value`, `terms`, and `id`:
 #'
 #' \describe{
 #'   \item{level}{character, the factor levels}
 #'   \item{value}{numeric, the encoding}
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' @template case-weights-supervised
 #'
 #' @references
diff --git a/R/lencode_mixed.R b/R/lencode_mixed.R
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
 #' (the selectors or variables selected), `value` and `component` is returned.
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' columns `level`, `value`, `terms`, and `id`:
 #'
 #' \describe{
 #'   \item{level}{character, the factor levels}
 #'   \item{value}{numeric, the encoding}
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' @template case-weights-supervised
 #'
diff --git a/R/pca_sparse.R b/R/pca_sparse.R
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
 #' (the selectors or variables selected), `value` and `component` is returned.
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' columns `terms`, `value`, `component`, and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{value}{numeric, variable loading}
 #'   \item{component}{character, principle component}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' ```{r, echo = FALSE, results="asis"}
 #' step <- "step_pca_sparse"
diff --git a/R/pca_sparse_bayes.R b/R/pca_sparse_bayes.R
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibblewith columns `terms`
 #'(the selectors or variables selected), `value` and`component` is returned.
 #' When you [`tidy()`][tidy.recipe()] this step, a tibbleis retruned with
 #'columns `terms`, `value`,`component`, and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{value}{numeric, variable loading}
 #'   \item{component}{character, principle component}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' ```{r, echo = FALSE, results="asis"}
 #' step <- "step_pca_sparse_bayes"
 #' result <- knitr::knit_child("man/rmd/tunable-args.Rmd")
diff --git a/R/pca_truncated.R b/R/pca_truncated.R
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, use either `type = "coef"` for
 #' the variable loadings per component or `type = "variance"` for how much
 #' variance each component accounts for.
 #' When you [`tidy()`][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`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{value}{numeric, variable loading}
 #'   \item{component}{character, principle component}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' If `type = "variance"` a tibble returned with 4 columns `terms`, `value`,
 #' `component` , and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, type of variance}
 #'   \item{value}{numeric, value of the variance}
 #'   \item{component}{integer, principle component}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' ```{r, echo = FALSE, results="asis"}
 #' step <- "step_pca_truncated"
diff --git a/R/umap.R b/R/umap.R
 #'
 #' # Tidying
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
 #' (the selectors or variables selected) is returned.
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #'  columns `terms` and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' ```{r, echo = FALSE, results="asis"}
 #' step <- "step_umap"
diff --git a/R/woe.R b/R/woe.R
 #'   predictors in a model.
 #' @param outcome The bare name of the binary outcome encased in `vars()`.
 #' @param dictionary A tbl. A map of levels and woe values. It must have the
 #'   same layout than the output returned from [dictionary()]. If `NULL`` the
 #'   same layout than the output returned from [dictionary()]. If `NULL` the
 #'   function will build a dictionary with those variables passed to \code{...}.
 #'   See [dictionary()] for details.
 #' @param Laplace The Laplace smoothing parameter. A value usually applied to
 #' `p_bad`, `p_good`, `woe` and `outcome` is returned.. See [dictionary()] for
 #' more information.
 #'
 #' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
 #' columns `terms` `value`, `n_tot`, `n_bad`, `n_good`, `p_bad`, `p_good`, `woe`
 #' and `outcome` and `id`:
 #'
 #' \describe{
 #'   \item{terms}{character, the selectors or variables selected}
 #'   \item{value}{character, level of the outcome}
 #'   \item{n_tot}{integer, total number}
 #'   \item{n_bad}{integer, number of bad examples}
 #'   \item{n_good}{integer, number of good examples}
 #'   \item{p_bad}{numeric, p of bad examples}
 #'   \item{p_good}{numeric, p of good examples}
 #'   \item{woe}{numeric, weight of evidence}
 #'   \item{outcome}{character, name of outcome variable}
 #'   \item{id}{character, id of this step}
 #' }
 #'
 #' ```{r, echo = FALSE, results="asis"}
 #' step <- "step_woe"
 #' result <- knitr::knit_child("man/rmd/tunable-args.Rmd")
diff --git a/man/step_collapse_cart.Rd b/man/step_collapse_cart.Rd
diff --git a/man/step_collapse_stringdist.Rd b/man/step_collapse_stringdist.Rd
diff --git a/man/step_discretize_cart.Rd b/man/step_discretize_cart.Rd
diff --git a/man/step_discretize_xgb.Rd b/man/step_discretize_xgb.Rd
Original file line number	Diff line number	Diff line change
Expand Up		@@ -2,14 +2,16 @@

		* `step_umap()` has gained `initial` and `target_weight` arguments. (#213)

		* Calling `?tidy.step_()` now sends you to the documentation for `step_()` where the outcome is documented. (#216)

		* Documentation for tidy methods for all steps has been improved to describe the return value more accurately. (#217)

		# embed 1.1.3

		* `step_collapse_stringdist()` will now return predictors as factors. (#204)

		* Fixed regression from 1.1.2 in `step_lencode_glm()` where it couldn't be used on multiple columns.

		* Calling `?tidy.step_()` now sends you to the documentation for `step_()` where the outcome is documented. (#216)

		# embed 1.1.2

		## Improvements
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Original file line number	Diff line number	Diff line change
Expand Up		@@ -41,11 +41,16 @@
		#' find any signal in the data.
		#'
		#' # Tidying
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `"terms"`
		#' (the column being modified), `"old"` (the old levels), `"new"` (the new
		#' levels), and `"id"`. If the CART model failed or could not find a good split,
		#' the requested predictor will not be in the results.
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
		#' columns `terms`, `old`, `new`, and `id`:
		#'
		#' \describe{
		#' \item{terms}{character, the selectors or variables selected}
		#' \item{old}{character, the old levels}
		#' \item{new}{character, the new levels}
		#' \item{id}{character, id of this step}
		#' }
		#'
		#' @template case-weights-not-supported
		#'
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Original file line number	Diff line number	Diff line change
Expand Up		@@ -27,10 +27,16 @@
		#' @details
		#'
		#' # Tidying
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `"terms"`
		#' (the column being modified), `"from"` (the old levels), `"to"` (the new
		#' levels), and `"id"`.
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
		#' columns `terms`, `from`, `to`, and `id`:
		#'
		#' \describe{
		#' \item{terms}{character, the selectors or variables selected}
		#' \item{from}{character, the old levels}
		#' \item{too}{character, the new levels}
		#' \item{id}{character, id of this step}
		#' }
		#'
		#' @template case-weights-not-supported
		#'
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Expand Up		@@ -45,9 +45,15 @@
		#' Note that the original data will be replaced with the new bins.
		#'
		#' # Tidying
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
		#' (the columns that is selected), `values` is returned.
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
		#' columns `terms`, `value`, and `id`:
		#'
		#' \describe{
		#' \item{terms}{character, the selectors or variables selected}
		#' \item{value}{numeric, location of the splits}
		#' \item{id}{character, id of this step}
		#' }
		#'
		#' ```{r, echo = FALSE, results="asis"}
		#' step <- "step_discretize_cart"
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Original file line number	Diff line number	Diff line change
Expand Up		@@ -62,9 +62,15 @@
		#' Note that the original data will be replaced with the new bins.
		#'
		#' # Tidying
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
		#' (the columns that is selected), `values` is returned.
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
		#' columns `terms`, `value`, and `id`:
		#'
		#' \describe{
		#' \item{terms}{character, the selectors or variables selected}
		#' \item{value}{numeric, location of the splits}
		#' \item{id}{character, id of this step}
		#' }
		#'
		#' ```{r, echo = FALSE, results="asis"}
		#' step <- "step_discretize_xgb"
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Original file line number	Diff line number	Diff line change
Expand Up		@@ -102,10 +102,16 @@
		#' this step with `caret`, avoid parallel processing.
		#'
		#' # Tidying
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
		#' (the selectors or variables selected), `levels` (levels in variable), and a
		#' number of columns with embedding information are returned.
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
		#' a number of columns with embedding information, and columns `terms`,
		#' `levels`, and `id`:
		#'
		#' \describe{
		#' \item{terms}{character, the selectors or variables selected}
		#' \item{levels}{character, levels in variable}
		#' \item{id}{character, id of this step}
		#' }
		#'
		#' ```{r, echo = FALSE, results="asis"}
		#' step <- "step_embed"
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Original file line number	Diff line number	Diff line change
Expand Up		@@ -34,9 +34,14 @@
		#' [recipes::step_zv()]) is recommended for any recipe that uses hashed columns.
		#'
		#' # Tidying
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
		#' (the columns that is selected) is returned.
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
		#' columns `terms` and `id`:
		#'
		#' \describe{
		#' \item{terms}{character, the selectors or variables selected}
		#' \item{id}{character, id of this step}
		#' }
		#'
		#' @template case-weights-not-supported
		#'
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Original file line number	Diff line number	Diff line change
Expand Up		@@ -61,9 +61,16 @@
		#'
		#' # Tidying
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
		#' (the selectors or variables selected), `value` and `component` is returned.
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
		#' columns `level`, `value`, `terms`, and `id`:
		#'
		#' \describe{
		#' \item{level}{character, the factor levels}
		#' \item{value}{numeric, the encoding}
		#' \item{terms}{character, the selectors or variables selected}
		#' \item{id}{character, id of this step}
		#' }
		#'
		#' @template case-weights-supervised
		#'
		#' @references
Expand All		@@ -78,7 +85,7 @@
		#' "Hierarchical Partial Pooling for Repeated Binary Trials"
		#' \url{https://tinyurl.com/stan-pooling}
		#'
		#' "Prior Distributions for `rstanarm`` Models"
		#' "Prior Distributions for `rstanarm` Models"
		#' \url{https://tinyurl.com/stan-priors}
		#'
		#' "Estimating Generalized (Non-)Linear Models with Group-Specific Terms with
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -44,9 +44,16 @@
		#'
		#' # Tidying
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
		#' (the selectors or variables selected), `value` and `component` is returned.
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
		#' columns `level`, `value`, `terms`, and `id`:
		#'
		#' \describe{
		#' \item{level}{character, the factor levels}
		#' \item{value}{numeric, the encoding}
		#' \item{terms}{character, the selectors or variables selected}
		#' \item{id}{character, id of this step}
		#' }
		#'
		#' @template case-weights-supervised
		#'
		#' @references
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Original file line number	Diff line number	Diff line change
Expand Up		@@ -57,8 +57,15 @@
		#'
		#' # Tidying
		#'
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble with columns `terms`
		#' (the selectors or variables selected), `value` and `component` is returned.
		#' When you [`tidy()`][tidy.recipe()] this step, a tibble is retruned with
		#' columns `level`, `value`, `terms`, and `id`:
		#'
		#' \describe{
		#' \item{level}{character, the factor levels}
		#' \item{value}{numeric, the encoding}
		#' \item{terms}{character, the selectors or variables selected}
		#' \item{id}{character, id of this step}
		#' }
		#'
		#' @template case-weights-supervised
		#'
Expand Down