Fit and subtract a baseline from a measurement signal

Usage

step_baseline(
  recipe,
  ...,
  role = NA,
  trained = FALSE,
  options = NULL,
  skip = FALSE,
  id = recipes::rand_id("measure")
)

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.
role: Assign the role of new variables.
trained: A logical to indicate if the quantities for preprocessing have been estimated.
options: A list of options to the default method for stats::prcomp(). Argument defaults are set to retx = FALSE, center = FALSE, scale. = FALSE, and tol = NULL. Note that the argument x should not be passed here (or at all).
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.