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step_shuffle
creates a specification of a recipe
step that will randomly change the order of rows for selected
variables.
step_shuffle(
recipe,
...,
role = NA,
trained = FALSE,
columns = NULL,
skip = FALSE,
id = rand_id("shuffle")
)
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 selections()
for more details.
Not used by this step since no new variables are created.
A logical to indicate if the quantities for preprocessing have been estimated.
A character string that contains the names of
columns that should be shuffled. These values are not determined
until prep()
is called.
A logical. Should the step be skipped when the
recipe is baked by bake()
? While all operations are baked
when prep()
is run, some operations may not be able to be
conducted on new data (e.g. processing the outcome variable(s)).
Care should be taken when using skip = TRUE
as it may affect
the computations for subsequent operations.
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 column
terms
(the columns that will be permuted) is returned.
Other row operation steps:
step_arrange()
,
step_filter()
,
step_impute_roll()
,
step_lag()
,
step_naomit()
,
step_sample()
,
step_slice()
# NOT RUN {
integers <- data.frame(A = 1:12, B = 13:24, C = 25:36)
library(dplyr)
rec <- recipe(~ A + B + C, data = integers) %>%
step_shuffle(A, B)
rand_set <- prep(rec, training = integers)
set.seed(5377)
bake(rand_set, integers)
tidy(rec, number = 1)
tidy(rand_set, number = 1)
# }
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