R recipes update_role_requirements 更新角色特定要求

update_role_requirements(recipe, role, ..., bake = NULL)

df <- tibble(y = c(1, 2, 3), x = c(4, 5, 6), var = c("a", "b", "c"))

# Let's assume that you have a `var` column that isn't used in the recipe.
# We typically recommend that you remove this column before passing the
# `data` to `recipe()`, but for now let's pass it through and assign it an
# `"id"` role.
rec <- recipe(y ~ ., df) %>%
  update_role(var, new_role = "id") %>%
  step_center(x)

prepped <- prep(rec, df)

# Now assume you have some "new data" and you are ready to `bake()` it
# to prepare it for prediction purposes. Here, you might not have `var`
# available as a column because it isn't important to your model.
new_data <- df[c("y", "x")]

# By default `var` is required at `bake()` time because we don't know if
# you actually use it in the recipe or not
try(bake(prepped, new_data))
#> Error in bake(prepped, new_data) : 
#>   The following required columns are missing from `new_data`: "var".
#> ℹ These columns have one of the following roles, which are required at `bake()` time: "id".
#> ℹ If these roles are not required at `bake()` time, use `update_role_requirements(role = "your_role", bake = FALSE)`.

# You can turn off this check by using `update_role_requirements()` and
# setting `bake = FALSE` for the `"id"` role. We recommend doing this on
# the original unprepped recipe, but it will also work on a prepped recipe.
rec <- update_role_requirements(rec, "id", bake = FALSE)
prepped <- prep(rec, df)

# Now you can `bake()` on `new_data` even though `var` is missing
bake(prepped, new_data)
#> # A tibble: 3 × 2
#>       x     y
#>   <dbl> <dbl>
#> 1    -1     1
#> 2     0     2
#> 3     1     3