check_range
creates a specification of a recipe
check that will check if the range of a numeric
variable changed in the new data.
Usage
check_range(
recipe,
...,
role = NA,
skip = FALSE,
trained = FALSE,
slack_prop = 0.05,
warn = FALSE,
lower = NULL,
upper = NULL,
id = rand_id("range_check_")
)
Arguments
- recipe
A recipe object. The check will be added to the sequence of operations for this recipe.
- ...
One or more selector functions to choose variables for this check. See
selections()
for more details.- role
Not used by this check since no new variables are created.
- skip
A logical. Should the check be skipped when the recipe is baked by
bake()
? While all operations are baked whenprep()
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 usingskip = TRUE
as it may affect the computations for subsequent operations.- trained
A logical for whether the selectors in
...
have been resolved byprep()
.- slack_prop
The allowed slack as a proportion of the range of the variable in the train set.
- warn
If
TRUE
the check will throw a warning instead of an error when failing.- lower
A named numeric vector of minimum values in the train set. This is
NULL
until computed byprep()
.- upper
A named numeric vector of maximum values in the train set. This is
NULL
until computed byprep()
.- id
A character string that is unique to this check to identify it.
Value
An updated version of recipe
with the new check added to the
sequence of any existing operations.
Details
The amount of slack that is allowed is determined by the
slack_prop
. This is a numeric of length one or two. If
of length one, the same proportion will be used at both ends
of the train set range. If of length two, its first value
is used to compute the allowed slack at the lower end,
the second to compute the allowed slack at the upper end.
Tidying
When you tidy()
this check, a tibble with columns
terms
(the selectors or variables selected) and value
(the means)
is returned.
See also
Other checks:
check_class()
,
check_cols()
,
check_missing()
,
check_new_values()
Examples
slack_df <- data_frame(x = 0:100)
#> Warning: `data_frame()` was deprecated in tibble 1.1.0.
#> ℹ Please use `tibble()` instead.
slack_new_data <- data_frame(x = -10:110)
# this will fail the check both ends
if (FALSE) { # \dontrun{
recipe(slack_df) %>%
check_range(x) %>%
prep() %>%
bake(slack_new_data)
} # }
# this will fail the check only at the upper end
if (FALSE) { # \dontrun{
recipe(slack_df) %>%
check_range(x, slack_prop = c(0.1, 0.05)) %>%
prep() %>%
bake(slack_new_data)
} # }
# give a warning instead of an error
if (FALSE) { # \dontrun{
recipe(slack_df) %>%
check_range(x, warn = TRUE) %>%
prep() %>%
bake(slack_new_data)
} # }