skipping.md
In recipes: Preprocessing and Feature Engineering Steps for Modeling

simple skip

Code
  prepped_2 <- prep(rec_1, training = iris, retain = FALSE)
Condition
  Warning:
  Since some operations have `skip = TRUE`, using `retain = TRUE` will allow those steps results to be accessible.

Code
  prep(rec_1, training = iris, retain = FALSE)
Condition
  Warning:
  Since some operations have `skip = TRUE`, using `retain = TRUE` will allow those steps results to be accessible.
Message

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 4

  -- Training information 
  Training data contained 150 data points and no incomplete rows.

  -- Operations 
  * Log transformation on: Sepal.Length | Trained
  * Dummy variables from: Species | Trained
  * Centering for: Sepal.Width, Petal.Length, Petal.Width, ... | Trained