step_relevel {recipes} | R Documentation |
Relevel factors to a desired level
Description
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.
Usage
step_relevel(
recipe,
...,
role = NA,
trained = FALSE,
ref_level,
objects = NULL,
skip = FALSE,
id = rand_id("relevel")
)
Arguments
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. |
Details
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.
Value
An updated version of recipe
with the new step added to the
sequence of any existing operations.
Tidying
When you tidy()
this step, a tibble is returned with
columns terms
, value
, and id
:
- terms
character, the selectors or variables selected
- value
character, the value of
ref_level
- id
character, id of this step
Case weights
The underlying operation does not allow for case weights.
See Also
Other dummy variable and encoding steps:
step_bin2factor()
,
step_count()
,
step_date()
,
step_dummy()
,
step_dummy_extract()
,
step_dummy_multi_choice()
,
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()
Examples
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)