View source: R/encoding_binary.R
step_encoding_binary | R Documentation |
step_encoding_binary()
creates a specification of a recipe step that will
perform binary encoding of factor variables.
step_encoding_binary(
recipe,
...,
role = NA,
trained = FALSE,
res = NULL,
columns = NULL,
keep_original_cols = FALSE,
skip = FALSE,
id = rand_id("encoding_binary")
)
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 are
affected by the 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. |
res |
A list containing levels of training variables is stored
here once this preprocessing step has be trained by |
columns |
A character string of variable names that will be populated
(eventually) by the |
keep_original_cols |
A logical to keep the original variables in the
output. Defaults to |
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 existing steps (if any). For the tidy
method, a tibble with
columns terms
(the columns that will be affected) and base
.
library(recipes)
library(modeldata)
data(ames)
rec <- recipe(~ Land_Contour + Neighborhood, data = ames) %>%
step_encoding_binary(all_nominal_predictors()) %>%
prep()
rec %>%
bake(new_data = NULL)
tidy(rec, 1)
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