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Gradient boosting improves model accuracy by iteratively adding weak learners—most commonly decision trees—where each new model focuses on correcting the errors made by the previous ones. By optimizing a loss function through gradient descent, the ensemble gradually becomes more accurate with each iteration. This approach is particularly…

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