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#' Create a Validation Split for 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()`.
#' @inheritParams rlang::args_dots_empty
#'
#' @return An tibble with classes `validation_set`, `rset`, `tbl_df`, `tbl`, and
#' `data.frame`. The results include a column for the data split object and a
#' column called `id` that has a character string with the resample identifier.
#' @export
#'
#' @examples
#' set.seed(1353)
#' car_split <- initial_validation_split(mtcars)
#' car_set <- validation_set(car_split)
validation_set <- function(split, ...) {
rlang::check_dots_empty()
train_and_val <- dplyr::bind_rows(
training(split),
validation(split)
)
n_train <- length(split$train_id)
val_split <- rsplit(
data = train_and_val,
in_id = seq_len(n_train),
out_id = NA
)
# this is same class as via the alternative `validation_split()`
class(val_split) <- c("val_split", "rsplit")
val_att <- attr(split, "val_att")
val_att[["origin_3way"]] <- TRUE
new_rset(
splits = list(val_split),
ids = "validation",
attrib = val_att,
subclass = c("validation_set", "rset")
)
}
# accessor methods for the rsplit -----------------------------------------
#' @rdname validation_set
#' @export
analysis.val_split <- function(x, ...) {
as.data.frame(x, data = "analysis", ...)
}
#' @rdname validation_set
#' @export
assessment.val_split <- function(x, ...) {
as.data.frame(x, data = "assessment", ...)
}
#' @rdname validation_set
#' @export
training.val_split <- function(x, ...) {
analysis(x, ...)
}
#' @rdname validation_set
#' @export
validation.val_split <- function(x, ...) {
assessment(x, ...)
}
#' @rdname validation_set
#' @export
testing.val_split <- function(x, ...) {
rlang::abort(
"The testing data is not part of the validation set object.",
i = "It is part of the result of the initial 3-way split, e.g., with `initial_validation_split()`."
)
}
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