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Boosting and Additive Trees 10.1 Boosting Methods Boosting is one of the most powerful learning ideas introduced in the last twenty years. It was originally designed for classication problems, but as will be seen in this chapter, it can protably be extended to regression as well. The motivation for boosting was a procedure that combines the
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In contrast, the use of decision stumps as the weak learners in the Boosting model made this method well equipped to handle mixed data: the decision split at each stump branch does not rely on any.
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