`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 = "sin", inverse = TRUE, columns = NULL, skip = FALSE, id = rand_id("hyperbolic") ) # S3 method for step_hyperbolic 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. |

func | A character value for the function. Valid values are "sin", "cos", or "tan". |

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. |

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`

(the
columns that will be affected), `inverse`

, and `func`

.

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 = "cos", inverse = FALSE) cos_obj <- prep(cos_trans, training = examples) transformed_te <- bake(cos_obj, examples) plot(examples$V1, transformed_te$V1)#> # A tibble: 1 x 4 #> terms inverse func id #> <chr> <lgl> <chr> <chr> #> 1 all_numeric_predictors() FALSE cos hyperbolic_IhS7o#> # A tibble: 2 x 4 #> terms inverse func id #> <chr> <lgl> <chr> <chr> #> 1 V1 FALSE cos hyperbolic_IhS7o #> 2 V2 FALSE cos hyperbolic_IhS7o