Inverse Transformation
step_inverse creates a specification of a recipe
step that will inverse transform the data.
step_inverse(
recipe,
...,
role = NA,
offset = 0,
trained = FALSE,
columns = NULL,
skip = FALSE,
id = rand_id("inverse")
)
## S3 method for class 'step_inverse'
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. |
offset |
An optional value to add to the data prior to
logging (to avoid |
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.
set.seed(313) examples <- matrix(runif(40), ncol = 2) examples <- data.frame(examples) rec <- recipe(~ X1 + X2, data = examples) inverse_trans <- rec %>% step_inverse(all_numeric_predictors()) inverse_obj <- prep(inverse_trans, training = examples) transformed_te <- bake(inverse_obj, examples) plot(examples$X1, transformed_te$X1) tidy(inverse_trans, number = 1) tidy(inverse_obj, number = 1)
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