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

many missing values

Code
  filtering_trained <- prep(filtering, training = dat2, verbose = FALSE)
Condition
  Warning:
  The correlation matrix has missing values. 1 columns were excluded from the filter.

occasional missing values

Code
  filtering_trained <- prep(filtering, training = dat3, verbose = FALSE)
Condition
  Warning:
  The correlation matrix has sporadic missing values. Some columns were excluded from the filter.

case weights

Code
  filtering_trained
Message

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

  -- Inputs 
  Number of variables by role
  predictor:    8
  case_weights: 1

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

  -- Operations 
  * Correlation filter on: V3_dup, V1, V2 | Trained, weighted

Code
  filtering_trained
Message

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

  -- Inputs 
  Number of variables by role
  predictor:    8
  case_weights: 1

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

  -- Operations 
  * Correlation filter on: V6, V1, V3 | Trained, ignored weights

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Correlation filter on: <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 
  * Correlation filter on: <none> | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 7

  -- Operations 
  * Correlation filter on: all_predictors()

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 7

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

  -- Operations 
  * Correlation filter on: V6, V1 | Trained