tests/testthat/_snaps/ratio.md

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

wrong type

Code
  prep(rec4, ex_dat, verbose = FALSE)
Condition
  Error in `step_ratio()`:
  Caused by error in `prep()`:
  x All columns selected for the step should be double or integer.
  * 1 factor variable found: `x5`

Code
  prep(rec5, ex_dat, verbose = FALSE)
Condition
  Error in `step_ratio()`:
  Caused by error in `prep()`:
  x All columns selected for the step should be double or integer.
  * 1 factor variable found: `x5`

Code
  prep(rec6, ex_dat, verbose = FALSE)
Condition
  Error in `step_ratio()`:
  Caused by error in `prep()`:
  x All columns selected for the step should be double or integer.
  * 1 factor variable found: `x5`

check_name() is used

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

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Ratios from: mpg

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 
  * Ratios from: <none> | Trained

keep_original_cols - can prep recipes with it missing

Code
  rec <- prep(rec)
Condition
  Warning:
  `keep_original_cols` was added to `step_ratio()` 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 
  * Ratios from: all_numeric() and all_numeric()

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 5

  -- Training information 
  Training data contained 10 data points and 1 incomplete row.

  -- Operations 
  * Ratios from: x2, x3, x4, x1, x1, x2, x3, x4 | Trained

topepo/recipes documentation built on April 10, 2024, 10:30 p.m.