Preference Order Argument in collinear()
Source:R/preference_order_collinear.R
preference_order_collinear.Rd
Internal function to manage the argument preference_order
in collinear()
.
Usage
preference_order_collinear(
df = NULL,
response = NULL,
predictors = NULL,
preference_order = NULL,
f = NULL,
quiet = FALSE
)
Arguments
- df
(required; data frame, tibble, or sf) A data frame with responses and predictors. Default: NULL.
- response
(optional; character string or vector) Name/s of response variable/s in
df
. Used in target encoding when it names a numeric variable and there are categorical predictors, and to compute preference order. Default: NULL.- predictors
(optional; character vector) Names of the predictors to select from
df
. If omitted, all numeric columns indf
are used instead. If argumentresponse
is not provided, non-numeric variables are ignored. Default: NULL- preference_order
(optional; string, character vector, output of
preference_order()
). Defines a priority order, from first to last, to preserve predictors during the selection process. Accepted inputs are:"auto" (default): if
response
is not NULL, callspreference_order()
for internal computation.character vector: predictor names in a custom preference order.
data frame: output of
preference_order()
fromresponse
of length one.named list: output of
preference_order()
fromresponse
of length two or more.NULL: disabled.
. Default: "auto"
- f
(optional: function) Function to compute preference order. If "auto" (default) or NULL, the output of
f_auto()
for the given data is used:f_auc_rf()
: ifresponse
is binomial.f_r2_pearson()
: ifresponse
andpredictors
are numeric.f_v()
: ifresponse
andpredictors
are categorical.f_v_rf_categorical()
: ifresponse
is categorical andpredictors
are numeric or mixed .f_r2_rf()
: in all other cases.
Default: NULL
- quiet
(optional; logical) If FALSE, messages generated during the execution of the function are printed to the console Default: FALSE
See also
Other preference_order_tools:
f_auto()
,
f_auto_rules()
,
f_functions()