How to Implement K-Fold Cross Validation in Epidemiology?
The implementation involves: 1. Data Splitting: Divide the dataset into k equally sized folds. 2. Model Training and Validation: Train the model on k-1 folds and validate it on the remaining fold. Repeat this k times. 3. Performance Metrics: Calculate performance metrics such as sensitivity, specificity, accuracy, and AUC for each iteration. 4. Averaging Results: Average the results to obtain a final performance estimate.
