Extract factor levels from a data frame
get_levels()
extracts the levels from any factor columns in data
. It is
mainly useful for extracting the original factor levels from the predictors
in the training set. get_outcome_levels()
is a small wrapper around
get_levels()
for extracting levels from a factor outcome
that first calls standardize()
on y
.
get_levels(data) get_outcome_levels(y)
data |
A data.frame to extract levels from. |
y |
The outcome. This can be:
|
A named list with as many elements as there are factor columns in data
or y
. The names are the names of the factor columns, and the values
are character vectors of the levels.
If there are no factor columns, NULL
is returned.
# Factor columns are returned with their levels get_levels(iris) # No factor columns get_levels(mtcars) # standardize() is first run on `y` # which converts the input to a data frame # with an automatically named column, `".outcome"` get_outcome_levels(y = factor(letters[1:5]))
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