step_logit {recipes} | R Documentation |
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") )
recipe |
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 |
offset |
A numeric value to modify values of the columns that are either
one or zero. They are modified to be |
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. |
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))
.
An updated version of recipe
with the new step added to the
sequence of any existing operations.
When you tidy()
this step, a tibble with columns
terms
(the columns that will be affected) is returned.
The underlying operation does not allow for case weights.
Other individual transformation steps:
step_BoxCox()
,
step_YeoJohnson()
,
step_bs()
,
step_harmonic()
,
step_hyperbolic()
,
step_inverse()
,
step_invlogit()
,
step_log()
,
step_mutate()
,
step_ns()
,
step_percentile()
,
step_poly()
,
step_relu()
,
step_sqrt()
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) tidy(logit_obj, number = 1)