LTM Limited Interview Question
What is the difference between Bagging and Boosting? Give examples and explain when to use each.
Interview Answer
Anonymous
Jul 2, 2025
Bagging: Models trained in parallel Reduces variance Example: Random Forest Best for: Overfitting problems 🟨 Boosting: Models trained sequentially Reduces bias Example: XGBoost, AdaBoost