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

outside argument

Code
  recipe(~a, data = train_df) %>% step_percentile(a, outside = "left") %>% prep() %>%
    bake(new_data = new_df)
Condition
  Error in `step_percentile()`:
  ! `outside` must be one of "none", "both", "upper", or "lower", not "left".

case weights

Code
  rec_trained
Message

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

  -- Inputs 
  Number of variables by role
  predictor:    8
  case_weights: 1

  -- Training information 
  Training data contained 456 data points and no incomplete rows.

  -- Operations 
  * Percentile transformation on: carbon, sulfur | Trained, weighted

Code
  rec_trained
Message

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

  -- Inputs 
  Number of variables by role
  predictor:    8
  case_weights: 1

  -- Training information 
  Training data contained 456 data points and no incomplete rows.

  -- Operations 
  * Percentile transformation on: carbon, sulfur | Trained, ignored weights

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Percentile 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 
  * Percentile transformation on: <none> | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 8

  -- Operations 
  * Percentile transformation on: carbon, sulfur

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 8

  -- Training information 
  Training data contained 456 data points and no incomplete rows.

  -- Operations 
  * Percentile transformation on: carbon, sulfur | Trained