step_discretize creates a specification of a recipe
step that will convert numeric data into a factor with
bins having approximately the same number of data points (based
on a training set).
step_discretize( recipe, ..., role = NA, trained = FALSE, num_breaks = 4, min_unique = 10, objects = NULL, options = list(), skip = FALSE, id = rand_id("discretize") ) # S3 method for step_discretize tidy(x, ...)
A recipe object. The step will be added to the sequence of operations for this recipe.
Not used by this step since no new variables are created.
A logical to indicate if the quantities for preprocessing have been estimated.
An integer defining how many cuts to make of the data.
An integer defining a sample size line of
dignity for the binning. If (the number of unique
A list of options to
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.
step_discretize returns an updated version of
recipe with the new step added to the sequence of
existing steps (if any). For the
tidy method, a tibble
terms (the selectors or variables selected)
value (the breaks).