Which ensemble method combines multiple weak learners trained sequentially, with each new model attempting to correct errors made by previous models?

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AStacking
BRandom Forest
CBoosting
DBagging

✓ Correct answer: C. Boosting Boosting is an ensemble technique that builds models sequentially, with each new model focusing on correcting the errors made by previous models. AdaBoost and Gradient Boosting are examples of boosting algorithms.

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Which ensemble method combines multiple weak learners trained sequentially, with each new model attempting to correct errors made by previous models?

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