In the field of epidemiology, stacking refers to the use of multiple statistical models or machine learning algorithms to improve the accuracy and robustness of predictions related to disease outbreaks, health trends, or other epidemiological phenomena. Stacking aims to combine the strengths of individual models to create a more comprehensive predictive framework.
