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

correct PCA values

Code
  tidy(pca_extract_trained, number = 3, type = "variances")
Condition
  Error in `match.arg()`:
  ! 'arg' should be one of "coef", "variance"

No PCA comps

Code
  print(pca_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 
  * No PCA components were extracted from: carbon, hydrogen, ... | Trained

backwards compatible with 0.1.17

Code
  pca_extract
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 for: carbon, hydrogen, oxygen, nitrogen, sulfur | Trained
  * Scaling for: carbon, hydrogen, oxygen, nitrogen, sulfur | Trained
  * PCA extraction with: carbon, hydrogen, oxygen, nitrogen, sulfur | Trained

check_name() is used

Code
  prep(rec, training = dat)
Condition
  Error in `step_pca()`:
  Caused by error in `bake()`:
  ! Name collision occured. The following variable names already exists:
  i  PC1

case weights

Code
  pca_extract_trained
Message

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

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

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

  -- Operations 
  * PCA extraction with: carbon, hydrogen, oxygen, sulfur | Trained, weighted

Code
  pca_extract_trained
Message

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

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

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

  -- Operations 
  * PCA extraction with: carbon, hydrogen, oxygen, ... | Trained, ignored weights

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * 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 
  * No PCA components were extracted 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_pca()` 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 
  * PCA extraction with: carbon, hydrogen, oxygen, nitrogen, sulfur

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 
  * PCA extraction with: carbon, hydrogen, oxygen, nitrogen, sulfur | Trained