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Exercise

Stacking the base learners

Given that many Machine Learning problems are quite challenging to solve for a single learning method, you ought to know how to build stronger solvers through the magic of ensemble models. Stacking is a simple yet quite powerful technique for building ensemble models. A stacked ensemble model is a meta-learner since it learns to predict the outcome not from the original data but from the predictions returned by the set of base learners.

In this exercise you will build a stacked ensemble out of the four base learners in models. The caret package has been preloaded and the control object holds the trainControl specs used to learn the base models.

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Question

What are the components of an stacked ensemble model?

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