tests/testthat/_snaps/novel.md

In tidymodels/recipes: Preprocessing and Feature Engineering Steps for Modeling

bad args

Code
  recipe(~., data = iris) %>% step_novel(all_predictors()) %>% prep(iris)
Condition
  Error in `step_novel()`:
  Caused by error in `prep()`:
  x All columns selected for the step should be string, factor, or ordered.
  * 4 double variables found: `Sepal.Length`, `Sepal.Width`, ...

Code
  recipe(~., data = tr_bad) %>% step_novel(all_predictors()) %>% prep(tr_bad)
Condition
  Error in `step_novel()`:
  Caused by error in `prep()`:
  ! Columns already contain the new level: x.

Code
  rec %>% step_novel(all_predictors(), new_level = letters) %>% prep()
Condition
  Error in `step_novel()`:
  Caused by error in `prep()`:
  ! `new_level` must be a single string, not a character vector.

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

Code
  bake(ex_1, new_data = tr_dat[, c(-3)])
Condition
  Error in `step_novel()`:
  ! The following required column is missing from `new_data`: x.

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Novel factor level assignment 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 
  * Novel factor level assignment for: <none> | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 5

  -- Operations 
  * Novel factor level assignment for: all_predictors()

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 5

  -- Training information 
  Training data contained 200 data points and no incomplete rows.

  -- Operations 
  * Novel factor level assignment for: v, w, x, y, z | Trained

tidymodels/recipes documentation built on Jan. 25, 2025, 7:30 a.m.