Merge pull request #519 from laurabrianna/declutter-reference-page

Fixes #475 - Documentation edits-decluttering the top of the refs page

NEWS.md

@@ -8,6 +8,8 @@
 
 * Removed trailing space in printing of `mc_cv()` objects (@ccani007, #464).
 
+* Improved documentation for `initial_split()` and friends (@laurabrianna, #519).
+
 ## Bug fixes
 
 * `vfold_cv()` now utilizes the `breaks` argument correctly for repeated cross-validation (@ZWael, #471).

R/initial_split.R

@@ -1,18 +1,20 @@
 #' Simple Training/Test Set Splitting
 #'
-#' `initial_split` creates a single binary split of the data into a training
-#'  set and testing set. `initial_time_split` does the same, but takes the
+#' `initial_split()` creates a single binary split of the data into a training
+#'  set and testing set. `initial_time_split()` does the same, but takes the
 #'  _first_ `prop` samples for training, instead of a random selection.
-#'  `group_initial_split` creates splits of the data based
+#'  `group_initial_split()` creates splits of the data based
 #'  on some grouping variable, so that all data in a "group" is assigned to
-#'  the same split.
-#'  `training` and `testing` are used to extract the resulting data.
+#'  the same split. 
+#' 
+#' @details `training()` and `testing()` are used to extract the resulting data.
+#'
 #' @template strata_details
 #' @inheritParams vfold_cv
 #' @inheritParams make_strata
 #' @param prop The proportion of data to be retained for modeling/analysis.
 #' @export
-#' @return An `rsplit` object that can be used with the `training` and `testing`
+#' @return An `rsplit` object that can be used with the `training()` and `testing()`
 #'  functions to extract the data in each split.
 #' @examplesIf rlang::is_installed("modeldata")
 #' set.seed(1353)
@@ -176,12 +178,12 @@ group_initial_split <- function(data, group, prop = 3 / 4, ..., strata = NULL, p
   attrib <- .get_split_args(res, allow_strata_false = TRUE)
 
   res <- res$splits[[1]]
-  
+
   attrib$times <- NULL
   for (i in names(attrib)) {
     attr(res, i) <- attrib[[i]]
   }
   class(res) <- c("group_initial_split", "initial_split", class(res))
-  
+
   res
 }

R/initial_validation_split.R

@@ -8,9 +8,10 @@
 #' `group_initial_validation_split()` creates similar random splits of the data
 #' based on some grouping variable, so that all data in a "group" are assigned
 #' to the same partition.
-#' `training()`, `validation()`, and `testing()` can be used to extract the
+#'
+#' @details [training()], [validation()], and [testing()] can be used to extract the
 #' resulting data sets.
-#' Use [`validation_set()`] to create an `rset` object for use with functions from
+#' Use [validation_set()] to create an `rset` object for use with functions from
 #' the tune package such as `tune::tune_grid()`.
 #'
 #' @template strata_details

R/validation_set.R

@@ -1,5 +1,7 @@
 #' Create a Validation Split for Tuning
 #'
+#' `validation_set()` creates a the validation split for model tuning.
+#'
 #' @param split An object of class `initial_validation_split`, such as resulting
 #' from [initial_validation_split()] or [group_initial_validation_split()].
 #' @param x An `rsplit` object produced by `validation_set()`.