# 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
make_discrim_flexible <- function() {
parsnip::set_model_engine("discrim_flexible", "classification", "earth")
parsnip::set_dependency("discrim_flexible", eng = "earth", pkg = "mda")
parsnip::set_dependency("discrim_flexible", eng = "earth", pkg = "earth")
parsnip::set_dependency("discrim_flexible", eng = "earth", pkg = "discrim")
parsnip::set_model_arg(
model = "discrim_flexible",
eng = "earth",
parsnip = "num_terms",
original = "nprune",
func = list(pkg = "dials", fun = "num_terms"),
has_submodel = TRUE
)
parsnip::set_model_arg(
model = "discrim_flexible",
eng = "earth",
parsnip = "prod_degree",
original = "degree",
func = list(pkg = "dials", fun = "prod_degree"),
has_submodel = FALSE
)
parsnip::set_model_arg(
model = "discrim_flexible",
eng = "earth",
parsnip = "prune_method",
original = "pmethod",
func = list(pkg = "dials", fun = "prune_method"),
has_submodel = FALSE
)
parsnip::set_fit(
model = "discrim_flexible",
eng = "earth",
mode = "classification",
value = list(
interface = "formula",
protect = c("formula", "data", "weights"),
func = c(pkg = "mda", fun = "fda"),
defaults = list(method = quote(earth::earth))
)
)
parsnip::set_encoding(
model = "discrim_flexible",
eng = "earth",
mode = "classification",
options = list(
predictor_indicators = "traditional",
compute_intercept = TRUE,
remove_intercept = TRUE,
allow_sparse_x = FALSE
)
)
parsnip::set_pred(
model = "discrim_flexible",
eng = "earth",
mode = "classification",
type = "class",
value = list(
pre = NULL,
post = NULL,
func = c(pkg = "discrim", fun = "pred_wrapper"),
args =
list(
object = quote(object$fit),
new_data = quote(new_data)
)
)
)
parsnip::set_pred(
model = "discrim_flexible",
eng = "earth",
mode = "classification",
type = "prob",
value = list(
pre = NULL,
post = prob_matrix_to_tibble,
func = c(pkg = "discrim", fun = "pred_wrapper"),
args =
list(
object = quote(object$fit),
new_data = quote(new_data),
type = "posterior"
)
)
)
parsnip::set_pred(
model = "discrim_flexible",
eng = "earth",
mode = "classification",
type = "raw",
value = list(
pre = NULL,
post = NULL,
func = c(fun = "predict"),
args =
list(
object = quote(object$fit),
newdata = quote(new_data)
)
)
)
}
# nocov end
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