Exercise

Train a boosted ensemble

Boosted ensemble models are among the most powerful machine learning methods that exist today. After you learned about the theoretical foundations, it's time to put these into practice. You will create a boosted model ensemble using the credit card customers training data.

Pre-loaded in your workspace are the training data customers_train and the boosted tree specification that you created previously, boost_spec.

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Train a boosted classification model on the customers_train tibble using still_customer as the response variable and all other columns as the predictor variables.