tests/testthat/_snaps/kpca.md

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

check_name() is used

Code
  prep(rec, training = dat)
Condition
  Error in `step_kpca()`:
  Caused by error in `bake()`:
  ! Name collision occurred. The following variable names already exist:
  * `kPC1`

No kPCA comps

Code
  pca_extract <- rec %>% step_kpca(X2, X3, X4, X5, X6, num_comp = 0, id = "") %>%
    prep()

Code
  pca_extract
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 5

  -- Training information 
  Training data contained 100 data points and no incomplete rows.

  -- Operations 
  * Kernel PCA extraction with: X2, X3, X4, X5, X6 | Trained

rethrows error correctly from implementation

Code
  recipe(~., data = mtcars) %>% step_kpca(all_predictors()) %>% prep()
Condition
  Error in `step_kpca()`:
  Caused by error in `prep()`:
  x Failed with error:
  i Error in kernlab::kpca(x = as.matrix(training[, col_names]), features = 5, : mocked error

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

Code
  bake(kpca_trained, new_data = te_dat[, 1:3])
Condition
  Error in `step_kpca()`:
  ! The following required columns are missing from `new_data`: X4, X5, and X6.

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Kernel PCA extraction with: <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 
  * Kernel PCA extraction with: <none> | Trained

keep_original_cols - can prep recipes with it missing

Code
  rec <- prep(rec)
Condition
  Warning:
  `keep_original_cols` was added to `step_kpca()` 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: 5

  -- Operations 
  * Kernel PCA extraction with: X2, X3, X4, X5, X6

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 5

  -- Training information 
  Training data contained 100 data points and no incomplete rows.

  -- Operations 
  * Kernel PCA extraction with: X2, X3, X4, X5, X6 | Trained

bad args

Code
  recipe(~., data = tr_dat) %>% step_kpca(all_numeric_predictors(), num_comp = -1) %>%
    prep()
Condition
  Error in `step_kpca()`:
  Caused by error in `prep()`:
  ! `num_comp` must be a whole number larger than or equal to 0, not the number -1.

Code
  recipe(~., data = tr_dat) %>% step_kpca(all_numeric_predictors(), prefix = 1) %>%
    prep()
Condition
  Error in `step_kpca()`:
  Caused by error in `prep()`:
  ! `prefix` must be a single string, not the number 1.

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