View source: R/dummy_multi_choice.R
step_dummy_multi_choice | R Documentation |
step_dummy_multi_choice()
creates a specification of a recipe step that
will convert multiple nominal data (e.g. characters or factors) into one or
more numeric binary model terms for the levels of the original data.
step_dummy_multi_choice(
recipe,
...,
role = "predictor",
trained = FALSE,
threshold = 0,
levels = NULL,
input = NULL,
other = "other",
naming = dummy_names,
prefix = NULL,
keep_original_cols = FALSE,
skip = FALSE,
id = rand_id("dummy_multi_choice")
)
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 |
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. |
threshold |
A numeric value between 0 and 1, or an integer greater or
equal to one. If less than one, then factor levels with a rate of
occurrence in the training set below |
levels |
A list that contains the information needed to
create dummy variables for each variable contained in
|
input |
A character vector containing the names of the columns used.
This is |
other |
A single character value for the "other" category. |
naming |
A function that defines the naming convention for new dummy columns. See Details below. |
prefix |
A character string for the prefix of the resulting new variables. See notes below. |
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. |
The overall proportion (or total counts) of the categories are
computed. The "other" category is used in place of any categorical levels
whose individual proportion (or frequency) in the training set is less than
threshold
.
This recipe step allows for flexible naming of the resulting
variables. For an unordered factor named x
, with levels "a"
and "b"
, the default naming convention would be to create a
new variable called x_b
. The naming format can be changed using
the naming
argument; the function dummy_names()
is the
default.
An updated version of recipe
with the new step added to the
sequence of any existing operations.
This step has 1 tuning parameters:
threshold
: Threshold (type: double, default: 0)
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()
,
step_factor2string()
,
step_holiday()
,
step_indicate_na()
,
step_integer()
,
step_novel()
,
step_num2factor()
,
step_ordinalscore()
,
step_other()
,
step_regex()
,
step_relevel()
,
step_string2factor()
,
step_time()
,
step_unknown()
,
step_unorder()
library(tibble)
languages <- tribble(
~lang_1, ~lang_2, ~lang_3,
"English", "Italian", NA,
"Spanish", NA, "French",
"Armenian", "English", "French",
NA, NA, NA
)
dummy_multi_choice_rec <- recipe(~., data = languages) %>%
step_dummy_multi_choice(starts_with("lang")) %>%
prep()
bake(dummy_multi_choice_rec, new_data = NULL)
tidy(dummy_multi_choice_rec, number = 1)
dummy_multi_choice_rec2 <- recipe(~., data = languages) %>%
step_dummy_multi_choice(starts_with("lang"),
prefix = "lang",
threshold = 0.2
) %>%
prep()
bake(dummy_multi_choice_rec2, new_data = NULL)
tidy(dummy_multi_choice_rec2, number = 1)
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