ica.md
In recipes: Preprocessing and Feature Engineering Steps for Modeling

No ICA comps

Code
  print(ica_extract_trained)
Message

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

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

  -- Training information 
  Training data contained 456 data points and no incomplete rows.

  -- Operations 
  * Centering and scaling for: carbon, hydrogen, oxygen, nitrogen, ... | Trained
  * No ICA components were extracted from: carbon, hydrogen, ... | Trained

check_name() is used

Code
  prep(rec, training = dat)
Condition
  Error in `step_ica()`:
  Caused by error in `bake()`:
  ! Name collision occured. The following variable names already exists:
  i  IC1

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * ICA 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 
  * ICA 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_ica()` after this recipe was created.
  Regenerate your recipe to avoid this warning.

printing

Code
  print(rec)
Message

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

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

  -- Operations 
  * Centering and scaling for: all_predictors()
  * ICA extraction with: carbon, hydrogen

Code
  prep(rec)
Message

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

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

  -- Training information 
  Training data contained 456 data points and no incomplete rows.

  -- Operations 
  * Centering and scaling for: carbon, hydrogen, oxygen, nitrogen, ... | Trained
  * ICA extraction with: carbon, hydrogen | Trained