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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.

This exercise is part of the course

Machine Learning with Tree-Based Models in R

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Train the model on the training set
boost_model <- fit(___,
                   ___,
                   ___)

boost_model
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