Ensemble Machine Learning
noun
Definition: A combination of multiple models whose predictions are aggregated (e.g., by voting, averaging, or stacking) to improve accuracy, robustness, or generalization compared with a single model [Google ML Glossary].
Example in context: “The ensemble is composed of a long/short-term memory (LSTM) network, a traditional Kalman filter, and a traditional linear regression model.” [Jamarani et al. 2024]
Related terms: ensemble model, committee model, bagging, boosting, stacking