What is Stacking?

Stacking is an ensemble machine learning technique that combines multiple base models to produce a more accurate predictive model. It works by training several diverse base models, then training a meta-model to learn how to best combine the predictions from the base models. This meta-model is trained on the out-of-sample predictions of the base models. It is commonly used to improve prediction accuracy and robustness compared to using a single model.