step_logit creates a specification of a recipe
step that will logit transform the data.
step_logit( recipe, ..., offset = 0, role = NA, trained = FALSE, columns = NULL, skip = FALSE, id = rand_id("logit") )
A recipe object. The step will be added to the sequence of operations for this recipe.
One or more selector functions to choose variables for this step. See
selections()for more details.
A numeric value to modify values of the columns that are either one or zero. They are modified to be
x - offsetor
Not used by this step since no new variables are created.
A logical to indicate if the quantities for preprocessing have been estimated.
A character string of variable names that will be populated (eventually) by the
A logical. Should the step be skipped when the recipe is baked by
bake()? While all operations are baked when
prep()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 using
skip = TRUEas it may affect the computations for subsequent operations.
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 any existing operations.
The logit transformation takes values between
zero and one and translates them to be on the real line using
f(p) = log(p/(1-p)).
tidy() this step, a tibble with columns
terms (the columns that will be affected) is returned.
set.seed(313) examples <- matrix(runif(40), ncol = 2) examples <- data.frame(examples) rec <- recipe(~ X1 + X2, data = examples) logit_trans <- rec %>% step_logit(all_numeric_predictors()) logit_obj <- prep(logit_trans, training = examples) transformed_te <- bake(logit_obj, examples) plot(examples$X1, transformed_te$X1) tidy(logit_trans, number = 1) #> # A tibble: 1 × 2 #> terms id #> <chr> <chr> #> 1 all_numeric_predictors() logit_ooyvr tidy(logit_obj, number = 1) #> # A tibble: 2 × 2 #> terms id #> <chr> <chr> #> 1 X1 logit_ooyvr #> 2 X2 logit_ooyvr