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  3. Machine Learning with Tree-Based Models in R

Exercise

Evaluate the ensemble

So far, so good. But how good exactly? Prove your model evaluation skills by cross-validating your out-of-sample AUC!

The specification boost_spec and the customers_train tibble are still loaded.

Instructions

100 XP
  • Create five CV folds of your training set and save them as folds.
  • Fit and evaluate a model that predicts still_customer for every fold, using your specification, all predictor variables, and the AUC metric.
  • Collect the metrics of cv_results and check the mean AUC.