# These functions define the Bagged Decision Tree Models.
# They are executed when this package is loaded via `.onLoad()` and modify the
# parsnip package's model environment.
# These functions are tested indirectly when the models are used. Since this
# function is executed on package startup, you can't execute them to test since
# they are already in the parsnip model database. We'll exclude them from
# coverage stats for this reason.
# nocov start
make_bag_tree_rpart <- function() {
parsnip::set_model_engine("bag_tree", mode = "censored regression", eng = "rpart")
parsnip::set_dependency(
"bag_tree",
eng = "rpart",
pkg = "ipred",
mode = "censored regression"
)
parsnip::set_dependency(
"bag_tree",
eng = "rpart",
pkg = "censored",
mode = "censored regression"
)
parsnip::set_fit(
model = "bag_tree",
eng = "rpart",
mode = "censored regression",
value = list(
interface = "formula",
protect = c("formula", "data", "weights"),
func = c(pkg = "ipred", fun = "bagging"),
defaults = list()
)
)
parsnip::set_encoding(
model = "bag_tree",
eng = "rpart",
mode = "censored regression",
options = list(
predictor_indicators = "none",
compute_intercept = FALSE,
remove_intercept = FALSE,
allow_sparse_x = FALSE
)
)
parsnip::set_pred(
model = "bag_tree",
eng = "rpart",
mode = "censored regression",
type = "time",
value = list(
pre = NULL,
post = NULL,
func = c(pkg = "censored", fun = "survival_time_survbagg"),
args =
list(
object = rlang::expr(object),
new_data = rlang::expr(new_data)
)
)
)
parsnip::set_pred(
model = "bag_tree",
eng = "rpart",
mode = "censored regression",
type = "survival",
value = list(
pre = NULL,
post = NULL,
func = c(pkg = "censored", fun = "survival_prob_survbagg"),
args =
list(
object = rlang::expr(object),
new_data = rlang::expr(new_data),
eval_time = rlang::expr(eval_time)
)
)
)
}
# nocov end
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