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

wrong vars

Code
  prep(rec2, training = examples, verbose = FALSE)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 2

  -- Training information 
  Training data contained 12 data points and no incomplete rows.

  -- Operations 
  * Unordered variables: X1, X2 | Trained

Code
  prep(rec3, training = examples, verbose = FALSE)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 2

  -- Training information 
  Training data contained 12 data points and no incomplete rows.

  -- Operations 
  * Unordered variables: X1 | Trained

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Unordered variables: <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 
  * Unordered variables: <none> | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 2

  -- Operations 
  * Unordered variables: X2

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 2

  -- Training information 
  Training data contained 12 data points and no incomplete rows.

  -- Operations 
  * Unordered variables: X2 | Trained