step_other {recipes} | R Documentation |
step_other
creates a specification of a recipe
step that will potentially pool infrequently occurring values
into an "other" category.
step_other(recipe, ..., role = NA, trained = FALSE, threshold = 0.05, other = "other", objects = NULL) ## S3 method for class 'step_other' tidy(x, ...)
recipe |
A recipe object. The step will be added to the sequence of operations for this recipe. |
... |
One or more selector functions to choose which
variables that will potentially be reduced. 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. |
threshold |
A single numeric value in (0, 1) for pooling. |
other |
A single character value for the "other" category. |
objects |
A list of objects that contain the information
to pool infrequent levels that is determined by
|
x |
A |
The overall proportion of the categories are computed. The "other"
category is used in place of any categorical levels whose individual
proportion in the training set is less than threshold
.
If no pooling is done the data are unmodified (although character data may
be changed to factors based on the value of stringsAsFactors
in
prep.recipe()
). Otherwise, a factor is always returned with
different factor levels.
If threshold
is less than the largest category proportion, all levels
except for the most frequent are collapsed to the other
level.
If the retained categories include the value of other
, an error is
thrown. If other
is in the list of discarded levels, no error
occurs.
An updated version of recipe
with the new step
added to the sequence of existing steps (if any). For the
tidy
method, a tibble with columns terms
(the
columns that will be affected) and retained
(the factor
levels that were not pulled into "other")
data(okc) set.seed(19) in_train <- sample(1:nrow(okc), size = 30000) okc_tr <- okc[ in_train,] okc_te <- okc[-in_train,] rec <- recipe(~ diet + location, data = okc_tr) rec <- rec %>% step_other(diet, location, threshold = .1, other = "other values") rec <- prep(rec, training = okc_tr) collapsed <- bake(rec, okc_te) table(okc_te$diet, collapsed$diet, useNA = "always") tidy(rec, number = 1)