step_regex {recipes} | R Documentation |
step_regex
creates a specification of a recipe step that will
create a new dummy variable based on a regular expression.
step_regex( recipe, ..., role = "predictor", trained = FALSE, pattern = ".", options = list(), result = make.names(pattern), input = NULL, skip = FALSE, id = rand_id("regex") )
recipe |
A recipe object. The step will be added to the sequence of operations for this recipe. |
... |
A single selector function to choose which variable
will be searched for the regex pattern. The selector should resolve
to a single variable. See |
role |
For model terms created by this step, what analysis role should they be assigned? By default, the new columns created by this step from the original variables will be used as predictors in a model. |
trained |
A logical to indicate if the quantities for preprocessing have been estimated. |
pattern |
A character string containing a regular
expression (or character string for |
options |
A list of options to |
result |
A single character value for the name of the new variable. It should be a valid column name. |
input |
A single character value for the name of the
variable being searched. This is |
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. |
An updated version of recipe
with the new step added to the
sequence of any existing operations.
When you tidy()
this step, a tibble with columns
terms
(the selectors or variables selected) and result
(the
new column name) is returned.
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_relevel()
,
step_string2factor()
,
step_time()
,
step_unknown()
,
step_unorder()
data(covers, package = "modeldata") rec <- recipe(~description, covers) %>% step_regex(description, pattern = "(rock|stony)", result = "rocks") %>% step_regex(description, pattern = "ratake families") rec2 <- prep(rec, training = covers) rec2 with_dummies <- bake(rec2, new_data = covers) with_dummies tidy(rec, number = 1) tidy(rec2, number = 1)