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Explain briefly: what is the Gradient Boosting algorithm?
Gradient Boosting is an algorithm that works through the additive joining of simple models - commonly called weak learners - into a single composite model. It attempts to gradually approximate the target function by such combination. Regression trees are the most commonly used weak learners in gradient boosting.
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