Nothing
make_cubist <- function() {
parsnip::set_model_engine("cubist_rules", "regression", "Cubist")
parsnip::set_dependency("cubist_rules", "Cubist", "Cubist", "regression")
parsnip::set_dependency("cubist_rules", "Cubist", "rules", "regression")
parsnip::set_fit(
model = "cubist_rules",
eng = "Cubist",
mode = "regression",
value = list(
interface = "data.frame",
protect = c("x", "y", "weights"),
func = c(pkg = "rules", fun = "cubist_fit"),
defaults = list()
)
)
parsnip::set_encoding(
model = "cubist_rules",
eng = "Cubist",
mode = "regression",
options = list(
predictor_indicators = "none",
compute_intercept = FALSE,
remove_intercept = FALSE,
allow_sparse_x = FALSE
)
)
parsnip::set_model_arg(
model = "cubist_rules",
eng = "Cubist",
parsnip = "committees",
original = "committees",
func = list(pkg = "rules", fun = "committees"),
has_submodel = FALSE
)
parsnip::set_model_arg(
model = "cubist_rules",
eng = "Cubist",
parsnip = "neighbors",
original = "neighbors",
func = list(pkg = "dials", fun = "neighbors"),
has_submodel = TRUE
)
parsnip::set_model_arg(
model = "cubist_rules",
eng = "Cubist",
parsnip = "max_rules",
original = "max_rules",
func = list(pkg = "rules", fun = "max_rules"),
has_submodel = FALSE
)
parsnip::set_pred(
model = "cubist_rules",
eng = "Cubist",
mode = "regression",
type = "numeric",
value = list(
pre = NULL,
post = NULL,
func = c(fun = "predict"),
args =
list(
object = rlang::expr(object$fit),
newdata = rlang::expr(new_data),
neighbors = rlang::expr(rules::get_neighbors(object$spec$args))
)
)
)
parsnip::set_pred(
model = "cubist_rules",
eng = "Cubist",
mode = "regression",
type = "raw",
value = list(
pre = NULL,
post = NULL,
func = c(fun = "predict"),
args =
list(
object = rlang::expr(object$fit),
newdata = rlang::expr(new_data),
neighbors = rlang::expr(rules::get_neighbors(object$spec$args))
)
)
)
}
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