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Gradient Boosting (GB/GBOOST) is an ensemble learning method that serially trains a series of weak learners (usually shallow decision trees), with each new tree fitting the residuals (i.e., the negative gradient direction) of the previous round's model predictions, thereby progressively reducing the overall loss.
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11/3/2026
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