step_logit
creates a specification of a recipe
step that will logit transform the data.
step_logit( recipe, ..., role = NA, trained = FALSE, columns = NULL, skip = FALSE, id = rand_id("logit") ) # S3 method for step_logit 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 |
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
which
is the columns that will be affected.
The logit transformation takes values between
zero and one and translates them to be on the real line using
the function f(p) = log(p/(1-p))
.
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_predictors()) logit_obj <- prep(logit_trans, training = examples) transformed_te <- bake(logit_obj, examples) plot(examples$X1, transformed_te$X1)#> # A tibble: 1 x 2 #> terms id #> <chr> <chr> #> 1 all_predictors() logit_ooyvr#> # A tibble: 2 x 2 #> terms id #> <chr> <chr> #> 1 X1 logit_ooyvr #> 2 X2 logit_ooyvr