What are the different types of ensemble methods in AI?

What are the different types of ensemble methods in AI?

Ensemble methods combine multiple models to improve performance. The main types are bagging, boosting, and stacking.

Can you explain bagging in more detail?

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

What about boosting? How does it work?

Boosting sequentially trains models, where each new model focuses on the errors made by the previous ones, improving accuracy.

And what is stacking?

Stacking combines different models and uses a meta-model to learn how to best combine their predictions.