Chapter 07.01: Bagging Ensembles
Bagging (bootstrap aggregation) is a method for combining many models into a meta-model which often works much better than its individual components. In this section, we present the basic idea of bagging and explain why and when bagging works.
Lecture video
Lecture slides
Quiz
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## Which statements are true?
- [x] Bagging works best for unstable learners.
- [ ] For stable estimation methods, bagging always reduces performance.