tests/testthat/_snaps/scale.md

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

scale by factor of 1 or 2

Code
  not_recommended_standardized_input <- rec %>% step_scale(carbon, id = "scale",
    factor = 3) %>% prep(training = biomass)
Condition
  Warning:
  Scaling `factor` should take either a value of 1 or 2, not 3.

na_rm argument works for step_scale

Code
  rec_no_na_rm <- recipe(~., data = mtcars_na) %>% step_scale(all_predictors(),
  na_rm = FALSE) %>% prep()
Condition
  Warning:
  Columns `mpg`, `cyl`, `disp`, and `hp` returned NaN, because variance cannot be calculated and scaling cannot be used. Consider avoiding `Inf` or `-Inf` values and/or setting `na_rm = TRUE` before normalizing.

warns on zv

Code
  prep(rec1)
Condition
  Warning:
  !  The following column has zero variance so scaling cannot be used: zero_variance.
  i Consider using ?step_zv (`?recipes::step_zv()`) to remove those columns before normalizing.
Message

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

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 6

  -- Training information 
  Training data contained 536 data points and no incomplete rows.

  -- Operations 
  * Scaling for: carbon, hydrogen, oxygen, nitrogen, sulfur, ... | Trained

warns when NaN is returned

Code
  prep(rec1)
Condition
  Warning:
  Column `sulfur` returned NaN, because variance cannot be calculated and scaling cannot be used. Consider avoiding `Inf` or `-Inf` values and/or setting `na_rm = TRUE` before normalizing.
Message

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

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

  -- Training information 
  Training data contained 536 data points and no incomplete rows.

  -- Operations 
  * Log transformation on: sulfur | Trained
  * Scaling for: sulfur | Trained

scaling with case weights

Code
  rec
Message

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

  -- Inputs 
  Number of variables by role
  outcome:      1
  predictor:    9
  case_weights: 1

  -- Training information 
  Training data contained 32 data points and no incomplete rows.

  -- Operations 
  * Scaling for: disp, hp, drat, wt, qsec, vs, am, ... | Trained, weighted

Code
  rec
Message

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

  -- Inputs 
  Number of variables by role
  outcome:      1
  predictor:    9
  case_weights: 1

  -- Training information 
  Training data contained 32 data points and no incomplete rows.

  -- Operations 
  * Scaling for: cyl, disp, hp, drat, qsec, vs, ... | Trained, ignored weights

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Scaling 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 
  * Scaling for: <none> | Trained

printing

Code
  print(rec)
Message

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

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

  -- Operations 
  * Scaling for: disp and wt

Code
  prep(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 
  * Scaling for: disp and wt | Trained

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