step_hyperbolic {recipes} | R Documentation |
step_hyperbolic
creates a specification of a
recipe step that will transform data using a hyperbolic
function.
step_hyperbolic( recipe, ..., role = NA, trained = FALSE, func = c("sinh", "cosh", "tanh"), inverse = TRUE, columns = NULL, skip = FALSE, id = rand_id("hyperbolic") )
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 |
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. |
func |
A character value for the function. Valid values are "sinh", "cosh", or "tanh". |
inverse |
A logical: should the inverse function be used? |
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. |
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), inverse
, and func
is
returned.
The underlying operation does not allow for case weights.
Other individual transformation steps:
step_BoxCox()
,
step_YeoJohnson()
,
step_bs()
,
step_harmonic()
,
step_inverse()
,
step_invlogit()
,
step_logit()
,
step_log()
,
step_mutate()
,
step_ns()
,
step_percentile()
,
step_poly()
,
step_relu()
,
step_sqrt()
set.seed(313) examples <- matrix(rnorm(40), ncol = 2) examples <- as.data.frame(examples) rec <- recipe(~ V1 + V2, data = examples) cos_trans <- rec %>% step_hyperbolic( all_numeric_predictors(), func = "cosh", inverse = FALSE ) cos_obj <- prep(cos_trans, training = examples) transformed_te <- bake(cos_obj, examples) plot(examples$V1, transformed_te$V1) tidy(cos_trans, number = 1) tidy(cos_obj, number = 1)