tests/testthat/_snaps/lda.md

In tidymodels/textrecipes: Extra 'Recipes' for Text Processing

check_name() is used

Code
  prep(rec, training = dat)
Condition
  Error in `step_lda()`:
  Caused by error in `bake()`:
  ! Name collision occurred. The following variable names already exist:
  * `lda_text_1`

bad args

Code
  prep(step_lda(recipe(~., data = mtcars), num_topics = -4))
Condition
  Error in `step_lda()`:
  Caused by error in `prep()`:
  ! `num_topics` must be a whole number larger than or equal to 0, not the number -4.

Code
  prep(step_lda(recipe(~., data = mtcars), prefix = NULL))
Condition
  Error in `step_lda()`:
  Caused by error in `prep()`:
  ! `prefix` must be a single string, not `NULL`.

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

Code
  bake(trained, new_data = tokenized_test_data[, -1])
Condition
  Error in `step_lda()`:
  ! The following required column is missing from `new_data`: medium.

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Text feature extraction 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 
  * Text feature extraction for: <none> | Trained

keep_original_cols - can prep recipes with it missing

Code
  rec <- prep(rec)
Condition
  Warning:
  `keep_original_cols` was added to `step_lda()` after this recipe was created.
  i Regenerate your recipe to avoid this warning.

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 5

  -- Operations 
  * Tokenization for: Species
  * Text feature extraction for: Species

Code
  prep(rec)
Condition
  Warning in `get_dtm()`:
  dtm has 0 rows. Empty iterator?
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 5

  -- Training information 
  Training data contained 150 data points and no incomplete rows.

  -- Operations 
  * Tokenization for: Species | Trained
  * Text feature extraction for: Species | Trained

tidymodels/textrecipes documentation built on June 12, 2025, 7:24 p.m.