Explain 'Bagging' (Bootstrap Aggregating).

Explain 'Bagging' (Bootstrap Aggregating).

Approach: Describe sampling with replacement to build multiple models.

An ensemble method where multiple versions of a model are trained on different bootstrap samples of the training data. The final prediction is the average (for regression) or majority vote (for classification).

Follow-up: How does it reduce variance?

Key concepts: bootstrap, variance reduction, parallel.