Convert Ordered Factors to Unordered Factors
step_unorder creates a specification of a recipe
step that will transform the data.
step_unorder(
recipe,
...,
role = NA,
trained = FALSE,
columns = NULL,
skip = FALSE,
id = rand_id("unorder")
)
## S3 method for class 'step_unorder'
tidy(x, ...)recipe |
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 are affected by the step. See |
role |
Not used by this step since no new variables are created. |
trained |
A logical to indicate if the quantities for preprocessing have been estimated. |
columns |
A character string of variable names that will
be populated (eventually) by the |
skip |
A logical. Should the step be skipped when the
recipe is baked by |
id |
A character string that is unique to this step to identify it. |
x |
A |
The factors level order is preserved during the transformation.
An updated version of recipe with the new step
added to the sequence of existing steps (if any). For the
tidy method, a tibble with columns terms (the
columns that will be affected).
lmh <- c("Low", "Med", "High")
examples <- data.frame(X1 = factor(rep(letters[1:4], each = 3)),
X2 = ordered(rep(lmh, each = 4),
levels = lmh))
rec <- recipe(~ X1 + X2, data = examples)
factor_trans <- rec %>%
step_unorder(all_nominal_predictors())
factor_obj <- prep(factor_trans, training = examples)
transformed_te <- bake(factor_obj, examples)
table(transformed_te$X2, examples$X2)
tidy(factor_trans, number = 1)
tidy(factor_obj, number = 1)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.