Lab 5 - k-fold cross-validation

Create a test-train rsplit object of mlc_churn using initial_split(). Use the arguments to set the proportions of the training data to be 80%. Stratify the sampling according to the churn variable.

1. Create a LDA model specification.
2. Create a 10-fold cross-validation split object.
3. Fit the model within each of the folds.
4. Extract the performance metrics for each fold.