Thank you Eli

Thanks a lot for this

ta

thanks

Thank you

Stacking is a technique that combines multiple classification or regression models via a meta-classifier or a meta-regressor. 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. While it can be done manually, as we did in the the last 2 times we retrained, SKlearn has a wonderful library, STackingRegressor that takes in your base learners and the meta learner as arguments.