lencode.md
In embed: Extra Recipes for Encoding Predictors

factor outcome - factor predictor

Code
  new_values_ch <- bake(class_test, new_data = new_dat_ch)
Condition
  Warning in `bake()`:
  ! There was 1 column that was a factor when the recipe was prepped:
  * `x3`
  i This may cause errors when processing new data.

factor outcome - character predictor

Code
  new_values <- bake(class_test, new_data = new_dat_ch)

numeric outcome - factor predictor

Code
  new_values_ch <- bake(reg_test, new_data = new_dat_ch)
Condition
  Warning in `bake()`:
  ! There was 1 column that was a factor when the recipe was prepped:
  * `x3`
  i This may cause errors when processing new data.

bad args

Code
  prep(step_lencode(recipe(Species ~ ., data = three_class), Sepal.Length,
  outcome = vars(Species)), training = three_class, retain = TRUE)
Condition
  Error in `step_lencode()`:
  Caused by error in `prep()`:
  x All columns selected for the step should be string, factor, or ordered.
  * 1 double variable found: `Sepal.Length`

Code
  prep(step_lencode(recipe(Species ~ ., data = three_class), Species, outcome = vars(
    logical)), training = three_class, retain = TRUE)
Condition
  Error in `step_lencode()`:
  Caused by error in `purrr::map()`:
  i In index: 1.
  i With name: Species.
  Caused by error in `.f()`:
  ! Only works nominal or numeric `outcome`, not a logical vector.

case weights

Code
  class_test
Message

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

  -- Inputs 
  Number of variables by role
  outcome:      1
  predictor:    3
  case_weights: 1

  -- Training information 
  Training data contained 500 data points and no incomplete rows.

  -- Operations 
  * Linear embedding for factors via GLM for: x3 | Trained, weighted

bake method errors when needed non-standard role columns are missing

Code
  bake(rec_trained, new_data = ex_dat[, -3])
Condition
  Error in `step_lencode()`:
  ! The following required column is missing from `new_data`: x3.

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Linear embedding for factors via GLM for: <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 
  * Linear embedding for factors via GLM for: <none> | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 3

  -- Operations 
  * Linear embedding for factors via GLM for: x3

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 3

  -- Training information 
  Training data contained 500 data points and no incomplete rows.

  -- Operations 
  * Linear embedding for factors via GLM for: x3 | Trained