step_relevel {recipes} | R Documentation |
step_relevel
creates a specification of a recipe
step that will reorder the provided factor columns so that
the level specified by ref_level is first. This is useful
for contr.treatment contrasts which take the first level as the
reference.
step_relevel( recipe, ..., role = NA, trained = FALSE, ref_level, objects = NULL, skip = FALSE, id = rand_id("relevel") )
recipe |
A recipe object. The step will be added to the sequence of operations for this recipe. |
... |
One or more selector functions to choose variables
for this step. See |
role |
Not used by this step since no new variables are created. |
trained |
A logical to indicate if the quantities for preprocessing have been estimated. |
ref_level |
A single character value that will be used to relevel the factor column(s) (if the level is present). |
objects |
A list of objects that contain the information
on factor levels that will be determined by |
skip |
A logical. Should the step be skipped when the
recipe is baked by |
id |
A character string that is unique to this step to identify it. |
The selected variables are releveled to a level
(given by ref_level
). Placing the ref_level
in the first
position.
Note that if the original columns are character, they will be converted to factors by this step.
An updated version of recipe
with the new step added to the
sequence of any existing operations.
The underlying operation does not allow for case weights.
Other dummy variable and encoding steps:
step_bin2factor()
,
step_count()
,
step_date()
,
step_dummy_extract()
,
step_dummy_multi_choice()
,
step_dummy()
,
step_factor2string()
,
step_holiday()
,
step_indicate_na()
,
step_integer()
,
step_novel()
,
step_num2factor()
,
step_ordinalscore()
,
step_other()
,
step_regex()
,
step_string2factor()
,
step_time()
,
step_unknown()
,
step_unorder()
data(Sacramento, package = "modeldata") rec <- recipe(~ city + zip, data = Sacramento) %>% step_unknown(city, new_level = "UNKNOWN") %>% step_relevel(city, ref_level = "UNKNOWN") %>% prep() data <- bake(rec, Sacramento) levels(data$city)