In the context of epidemiology, ensemble methods offer several advantages: 1. Improved Accuracy: By combining multiple models, ensemble methods can reduce the error rates and enhance the overall predictive accuracy. 2. Robustness: They provide more stable predictions by mitigating the risks associated with individual model biases or errors. 3. Complexity Handling: Ensemble methods can capture the complex relationships between various epidemiological factors better than single models.
