`step_hyperbolic()`

creates a *specification* of a recipe step that will
transform data using a hyperbolic function.

## Arguments

- 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

`selections()`

for more details.- 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 the selected variable names. This field is a placeholder and will be populated once

`prep()`

is used.- skip
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 = TRUE`

as it may affect the computations for subsequent operations.- id
A character string that is unique to this step to identify it.

## Value

An updated version of `recipe`

with the new step added to the
sequence of any existing operations.

## Tidying

When you `tidy()`

this step, a tibble is returned with
columns `terms`

, `inverse`

, `func`

, and `id`

:

- terms
character, the selectors or variables selected

- inverse
logical, is the inverse function be used

- func
character, name of function.

`"sinh"`

,`"cosh"`

, or`"tanh"`

- id
character, id of this step

## See also

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()`

## Examples

```
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)
#> # A tibble: 1 × 4
#> terms inverse func id
#> <chr> <lgl> <chr> <chr>
#> 1 all_numeric_predictors() FALSE cosh hyperbolic_IhS7o
tidy(cos_obj, number = 1)
#> # A tibble: 2 × 4
#> terms inverse func id
#> <chr> <lgl> <chr> <chr>
#> 1 V1 FALSE cosh hyperbolic_IhS7o
#> 2 V2 FALSE cosh hyperbolic_IhS7o
```