Ensemble Methods

Cascade models route inputs to progressively more expensive models, but only one model makes the final decision at each stage.

Ensemble methods take the opposite approach: run multiple models on the same input and combine their predictions. An ensemble helps when the models make different errors. If the models are highly correlated, the ensemble mostly adds cost.