step_relevel creates a specification of a recipe
step that will reorder the provided factor columns so that
the level specified by ref_level is first. This is useful
for contr.treatment contrasts which take the first level as the
step_relevel( recipe, ..., role = NA, trained = FALSE, ref_level, objects = NULL, skip = FALSE, id = rand_id("relevel") ) # S3 method for step_relevel tidy(x, ...)
A recipe object. The step will be added to the sequence of operations for this recipe.
One or more selector functions to choose which
variables that will be affected by the step. These variables
should be character or factor types. See
Not used by this step since no new variables are created.
A logical to indicate if the quantities for preprocessing have been estimated.
A single character value that will be used to relevel the factor column(s) (if the level is present).
A list of objects that contain the information
on factor levels that will be determined by
A logical. Should the step be skipped when the
recipe is baked by
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 existing steps (if any).
The selected variables are releveled to a level
ref_level). Placing the
ref_level in the first
Note that if the original columns are character, they will be converted to factors by this step.
library(modeldata) data(okc) rec <- recipe(~ diet + location, data = okc) %>% step_unknown(diet, new_level = "UNKNOWN") %>% step_relevel(diet, ref_level = "UNKNOWN") %>% prep() data <- bake(rec, okc) levels(data$diet)#>  "UNKNOWN" "anything" "halal" #>  "kosher" "mostly anything" "mostly halal" #>  "mostly kosher" "mostly other" "mostly vegan" #>  "mostly vegetarian" "other" "strictly anything" #>  "strictly halal" "strictly kosher" "strictly other" #>  "strictly vegan" "strictly vegetarian" "vegan" #>  "vegetarian"