address missing crossrefs WARNING

Author: simonpcouch

R/adjust-numeric-calibration.R

@@ -16,7 +16,7 @@
 #' @section Data Usage:
 #' This adjustment requires estimation and, as such, different subsets of data
 #' should be used to train it and evaluate its predictions. See the section
-#' by the same name in [workflows::add_tailor()] for more information on
+#' by the same name in `?workflows::add_tailor()` for more information on
 #' preventing data leakage with postprocessors that require estimation. When
 #' situated in a workflow, tailors will automatically be estimated with
 #' appropriate subsets of data.

R/tailor.R

@@ -17,21 +17,21 @@
 #' Tailors must be trained with [fit()][fit.tailor()] before being applied to
 #' new data with [predict()][predict.tailor()]. Tailors are tightly integrated
 #' with the [tidymodels](https://tidymodels.org) framework; for greatest ease
-#' of use, situate tailors in model workflows with [workflows::add_tailor()].
+#' of use, situate tailors in model workflows with `?workflows::add_tailor()`.
 #'
 #' @param type Character. The model sub-mode. Possible values are
 #' `"unknown"`, `"regression"`, `"binary"`, or `"multiclass"`. Only required
-#' when used independently of [workflows::add_tailor()].
+#' when used independently of `?workflows::add_tailor()`.
 #' @param outcome <[`tidy-select`][dplyr::dplyr_tidy_select]> Only required
-#' when used independently of [workflows::add_tailor()], and can also be passed
+#' when used independently of `?workflows::add_tailor()`, and can also be passed
 #' at `fit()` time instead. The column name of the outcome variable.
 #' @param estimate <[`tidy-select`][dplyr::dplyr_tidy_select]> Only required
-#' when used independently of [workflows::add_tailor()], and can also be passed
+#' when used independently of `?workflows::add_tailor()`, and can also be passed
 #' at `fit()` time instead. The column name of the point estimate (e.g. predicted
 #' class), In tidymodels, this corresponds to column names `.pred`,
 #' `.pred_class`, or `.pred_time`.
 #' @param probabilities <[`tidy-select`][dplyr::dplyr_tidy_select]> Only required
-#' when used independently of [workflows::add_tailor()] for the `"binary"` or
+#' when used independently of `?workflows::add_tailor()` for the `"binary"` or
 #' `"multiclass"` types, and can also be passed at `fit()` time instead.
 #' The column names of class probability estimates. These should be given in
 #' the order of the factor levels of the `estimate`.
@@ -134,7 +134,7 @@ print.tailor <- function(x, ...) {
 #' added to a tailor, in the order in which they were applied.
 #'
 #' Users do not need to interface with these methods directly when tailors
-#' are situated inside model workflows with [workflows::add_tailor()].
+#' are situated inside model workflows with `?workflows::add_tailor()`.
 #'
 #' @section Data Usage:
 #'
@@ -143,7 +143,7 @@ print.tailor <- function(x, ...) {
 #' For others, as in [adjust_numeric_calibration()], adjustments actually
 #' learn from data; in that case, separate subsets of data ought to be used
 #' for training the tailor and evaluating its performance on predictions.
-#' See the Data Usage section in [workflows::add_tailor()] for more information
+#' See the Data Usage section in `?workflows::add_tailor()` for more information
 #' on how tidymodels makes that split; when situated in a model workflow,
 #' tailors will automatically be trained on the appropriate subset of data.
 #'