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Understanding the Math behind the XGBoost Algorithm – Each of these additive learners, h m (x), will make use of the residuals from the preceding function, F m-1 (x). The MSEs for F 0 (x), F 1 (x) and F 2 (x) are 875, 692 and 540. It’s amazing how these simple weak learners can bring about a huge reduction in error! Note that each learner, h m (x), is trained on the residuals. All the additive learners in boosting are modeled after the residual errors at each step.
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