remove rpart_train()

NAMESPACE

@@ -312,7 +312,6 @@ export(rand_forest)
 export(repair_call)
 export(req_pkgs)
 export(required_pkgs)
-export(rpart_train)
 export(rule_fit)
 export(set_args)
 export(set_dependency)

NEWS.md

@@ -23,6 +23,8 @@
 
 * Aligned `null_model()` with other model types; the model type now has an engine argument that defaults to `"parsnip"` and is checked with the same machinery that checks other model types in the package (#1083).
 
+* The deprecated function `rpart_train()` was removed after its deprecation period (#1044).
+
 ## Bug Fixes
 
 * Make sure that parsnip does not convert ordered factor predictions to be unordered.

R/decision_tree.R

@@ -129,76 +129,3 @@ translate.decision_tree <- function(x, engine = x$engine, ...) {
 check_args.decision_tree <- function(object, call = rlang::caller_env()) {
   invisible(object)
 }
-
-# ------------------------------------------------------------------------------
-
-#' Decision trees via rpart
-#'
-#' @description
-#' `rpart_train()` is a wrapper for `rpart()` tree-based models
-#'  where all of the model arguments are in the main function.
-#'
-#'  The function is now deprecated, as parsnip uses `rpart::rpart()` directly.
-#'
-#' @param formula A model formula.
-#' @param data A data frame.
-#' @param cp A non-negative number for complexity parameter. Any split
-#'  that does not decrease the overall lack of fit by a factor of
-#'  `cp` is not attempted. For instance, with anova splitting,
-#'  this means that the overall R-squared must increase by `cp` at
-#'  each step. The main role of this parameter is to save computing
-#'  time by pruning off splits that are obviously not worthwhile.
-#'  Essentially, the user informs the program that any split which
-#'  does not improve the fit by `cp` will likely be pruned off by
-#'  cross-validation, and that hence the program need not pursue it.
-#' @param weights Optional case weights.
-#' @param minsplit An integer for the minimum number of observations
-#'  that must exist in a node in order for a split to be attempted.
-#' @param maxdepth An integer for the maximum depth of any node
-#'  of the final tree, with the root node counted as depth 0.
-#'  Values greater than 30 `rpart` will give nonsense results on
-#'  32-bit machines. This function will truncate `maxdepth` to 30 in
-#'  those cases.
-#' @param ... Other arguments to pass to either `rpart` or `rpart.control`.
-#' @return A fitted rpart model.
-#' @keywords internal
-#' @export
-rpart_train <-
-  function(formula, data, weights = NULL, cp = 0.01, minsplit = 20, maxdepth = 30, ...) {
-    lifecycle::deprecate_warn(
-      "1.2.0",
-      "rpart_train()",
-      details = 'Instead, use `decision_tree(engine = "rpart")` or `rpart::rpart()` directly.'
-    )
-
-    bitness <- 8 * .Machine$sizeof.pointer
-    if (bitness == 32 & maxdepth > 30)
-      maxdepth <- 30
-
-    other_args <- list(...)
-    protect_ctrl <- c("minsplit", "maxdepth", "cp")
-    protect_fit <- NULL
-    f_names <- names(formals(getFromNamespace("rpart", "rpart")))
-    c_names <- names(formals(getFromNamespace("rpart.control", "rpart")))
-    other_args <- other_args[!(other_args %in% c(protect_ctrl, protect_fit))]
-    ctrl_args <- other_args[names(other_args) %in% c_names]
-    fit_args <- other_args[names(other_args) %in% f_names]
-
-    ctrl <- call2("rpart.control", .ns = "rpart")
-    ctrl$minsplit <- minsplit
-    ctrl$maxdepth <- maxdepth
-    ctrl$cp <- cp
-    ctrl <- rlang::call_modify(ctrl, !!!ctrl_args)
-
-    fit_call <- call2("rpart", .ns = "rpart")
-    fit_call$formula <- expr(formula)
-    fit_call$data <- expr(data)
-    fit_call$control <- ctrl
-    if (!is.null(weights)) {
-      fit_call$weights <- quote(weights)
-    }
-    fit_call <- rlang::call_modify(fit_call, !!!fit_args)
-
-    eval_tidy(fit_call)
-  }
-

R/misc.R

@@ -602,7 +602,7 @@
   }
 
   if (inherits(x, "workflow")) {
-    x <- x %>% extract_fit_parsnip(x)
+    x <- x %>% hardhat::extract_fit_parsnip(x)
   }
   model_spec <- extract_spec_parsnip(x)
   model_engine <- model_spec$engine

tests/testthat/test-decision_tree.R

@@ -25,16 +25,6 @@ test_that('bad input', {
   )
 })
 
-test_that('rpart_train is stop-deprecated when it ought to be (#1044)', {
-  skip_on_cran()
-
-  # once this test fails, transition `rpart_train()` to `deprecate_stop()`
-  # and transition this test to fail if `rpart_train()` still exists after a year.
-  if (Sys.Date() > "2025-01-01") {
-    expect_snapshot(error = TRUE, rpart_train(mpg ~ ., mtcars))
-  }
-})
-
 # ------------------------------------------------------------------------------
 
 test_that('argument checks for data dimensions', {