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

missing data

Code
  prep(rec_false, training = ex_dat, verbose = FALSE)
Condition
  Error in `step_YeoJohnson()`:
  Caused by error in `prep()`:
  ! Missing values are not allowed for the YJ transformation. See `na_rm` option

empty printing

Code
  rec
Message

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

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 10

  -- Operations 
  * Yeo-Johnson transformation on: <none>

Code
  rec
Message

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

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 10

  -- Training information 
  Training data contained 32 data points and no incomplete rows.

  -- Operations 
  * Yeo-Johnson transformation on: <none> | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 4

  -- Operations 
  * Yeo-Johnson transformation on: x1, x2, x3, x4

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 4

  -- Training information 
  Training data contained 20 data points and no incomplete rows.

  -- Operations 
  * Yeo-Johnson transformation on: x1, x2, x4 | Trained