Recipe step for basis expansions — step

step_basis() is a single function that creates a specification of a recipe step that will create new columns that are basis expansions, using any of the basis expansion functions in this package.

Usage

step_basis(
  recipe,
  ...,
  role = NA,
  trained = FALSE,
  fn = NULL,
  options = list(),
  object = NULL,
  prefix = deparse(substitute(fn)),
  skip = FALSE,
  id = recipes::rand_id("basis")
)

Arguments

recipe: A recipe object.
...: One or more selector functions to choose variables for this step. See recipes::selections() for more details.
role: For model terms created by this step, what analysis role should they be assigned? By default, the new columns created by this step from the original variables will be used as predictors in a model.
trained: A logical to indicate if the quantities for preprocessing have been estimated.
fn: The basis function to use, e.g., b_rff().
options: A list of options for the basis function fn.
object: The basis object created once the step has been trained.
prefix: The prefix to use for the new column names. Numbers will be appended, per recipes::names0(), to create column names.
skip: A logical. Should the step be skipped when the recipe is baked by recipes::bake()?
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.

Tuning Parameters

There are no tuning parameters made available to the tunable interface.

Case Weights

The underlying operation does not use case weights.

Examples

rec = recipes::recipe(depth ~ lat + long + mag, quakes)
rec_rff = step_basis(rec, lat, long, fn = b_rff,
                     options = list(p = 5, kernel = k_rbf(2), stdize="none"))
recipes::bake(recipes::prep(rec_rff), new_data=NULL)
#> # A tibble: 1,000 × 7
#>      mag depth b_rff1 b_rff2 b_rff3 b_rff4  b_rff5
#>    <dbl> <int>  <dbl>  <dbl>  <dbl>  <dbl>   <dbl>
#>  1   4.8   562 -0.361  0.121 -0.302  0.351 -0.0812
#>  2   4.2   650 -0.297  0.111 -0.428  0.370 -0.178 
#>  3   5.4    42  0.404 -0.331  0.428 -0.398 -0.175 
#>  4   4.1   626 -0.390 -0.397 -0.260  0.423  0.411 
#>  5   4     649 -0.379  0.154 -0.189  0.325 -0.0512
#>  6   4     195 -0.431  0.203  0.444  0.218  0.307 
#>  7   4.8    82 -0.438 -0.425 -0.441  0.349  0.446 
#>  8   4.4   194  0.249 -0.447 -0.299 -0.318  0.414 
#>  9   4.7   211  0.115 -0.432 -0.357 -0.245  0.447 
#> 10   4.3   622 -0.425 -0.430 -0.285  0.212  0.383 
#> # ℹ 990 more rows