What are ensemble methods in Python?

What are ensemble methods in Python?

Ensemble methods combine multiple models to improve performance. Common techniques include bagging, boosting, and stacking.

Can you explain how bagging works?

Bagging, or Bootstrap Aggregating, involves training multiple models on different subsets of the data and averaging their predictions.

What about boosting? How is it different from bagging?

Boosting sequentially trains models, each focusing on the errors of the previous one, while bagging trains models independently.

Which ensemble method is generally more effective?

It depends on the problem, but boosting often yields better accuracy, especially for complex datasets.