How is Cross Validation Implemented in Epidemiological Studies?
To implement cross validation in epidemiological studies, researchers typically follow these steps:
Data Preparation: Clean and preprocess the data, handling missing values and normalizing features as necessary. Partitioning the Data: Split the dataset into training and testing subsets according to the chosen cross validation method. Model Training: Train the model on the training subsets. Model Testing: Test the model on the testing subsets and record the performance metrics. Performance Evaluation: Aggregate the performance metrics across all folds to get an overall assessment of the model's predictive ability.
