Boosting reduces bias and variance by building a sequence of weak learners and combining them into a strong __________.
- Learner
- Model
- Predictor
- nan
Boosting combines a sequence of weak learners into a strong learner by iteratively correcting the mistakes of previous models and giving more weight to the misclassified instances, resulting in reduced bias and variance.
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