Architecture of a stacking model

Data Science, AI and ML
#1

The architecture of a stacking model involves two or more base models, often referred to as level-0 models, and a meta-model that combines the predictions of the base models, referred to as a level-1 model. The meta-model is trained on the predictions made by base models on out-of-sample data.

Level-0 Models (Base-Models): Models fit on the training data and whose predictions are compiled.
Level-1 Model (Meta-Model): Model that learns how to best combine the predictions of the base models.