Why is Time Series Cross Validation Important in Epidemiology?
The primary reason time series cross validation is important in epidemiology is that it allows researchers to account for the temporal dependencies inherent in disease data. For example, the incidence of influenza cases in one week is likely to be influenced by the incidence in the preceding weeks. Traditional cross-validation methods, which randomly shuffle data, would disrupt these dependencies and lead to misleading performance metrics.
