tests/testthat/_snaps/classdist.md

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

check_name() is used

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

case weights

Code
  recipes:::get_center(mtcars, wts = wts, mfun = median)
Condition
  Error in `recipes:::get_center()`:
  ! The centering function requested cannot be used with case weights.

Code
  recipes:::get_both(mtcars, wts = wts, mfun = median)
Condition
  Error in `recipes:::get_both()`:
  ! The centering function requested cannot be used with case weights.

Code
  recipes:::get_both(mtcars, wts = wts, cfun = mad)
Condition
  Error in `recipes:::get_both()`:
  ! The variance function requested cannot be used with case weights.

Code
  rec_prep
Message

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

  -- Inputs 
  Number of variables by role
  outcome:      1
  predictor:    4
  case_weights: 1

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

  -- Operations 
  * Distances to Species for: Sepal.Length, ... | Trained, weighted

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

Code
  bake(trained, new_data = iris[, c(-3)])
Condition
  Error in `step_classdist()`:
  ! The following required column is missing from `new_data`: Petal.Length.

empty printing

Code
  rec
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 4

  -- Operations 
  * Distances to Species for: <none>

Code
  rec
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 4

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

  -- Operations 
  * Distances to Species 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_classdist()` 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
  outcome:   1
  predictor: 4

  -- Operations 
  * Distances to Species for: all_predictors()

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 4

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

  -- Operations 
  * Distances to Species for: Sepal.Length and Sepal.Width, ... | Trained

bad args

Code
  recipe(Species ~ ., data = iris) %>% step_classdist(all_predictors(), class = "Species",
  mean_func = 2) %>% prep()
Condition
  Error in `step_classdist()`:
  Caused by error in `prep()`:
  ! `x$mean_func` must be a function, not the number 2.

Code
  recipe(Species ~ ., data = iris) %>% step_classdist(all_predictors(), class = "Species",
  cov_func = NULL) %>% prep()
Condition
  Error in `step_classdist()`:
  Caused by error in `prep()`:
  ! `x$cov_func` must be a function, not `NULL`.

Code
  recipe(Species ~ ., data = iris) %>% step_classdist(all_predictors(), class = "Species",
  prefix = NULL) %>% prep()
Condition
  Error in `step_classdist()`:
  Caused by error in `prep()`:
  ! `x$prefix` must be a single string, not `NULL`.

Code
  recipe(Species ~ ., data = iris) %>% step_classdist(all_predictors(), class = "Species",
  pool = NULL) %>% prep()
Condition
  Error in `step_classdist()`:
  Caused by error in `prep()`:
  ! `x$pool` must be `TRUE` or `FALSE`, not `NULL`.

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