Stacking

Stacking is an ensemble learning technique that uses a meta-learning algorithm to learn how to best combine the predictions from two or more base machine learning algorithms. The base level models are trained based on a complete training set, then the meta-model is trained on the outputs of the base level model as features.

Stacking is a key component of any successful machine learning project, as it can help to improve the performance of your models.