Ensemble Methods

Summary

Combining multiple models' predictions to improve accuracy and robustness — bagging (random forests), boosting (XGBoost), and stacking (combining different model types) are the three main families.

• 1Compare bagging and boosting conceptually — what error each is designed to reduce.
• 2Try a simple stacking approach: combine predictions from 2-3 different model types.
• 3Learn why ensembles tend to generalize better than any single strong model.