Development and Evaluation of the Final Mortality Predictive Model

These steps yielded an optimally performing set of features with an acceptable level of missing values, and among them, the best-performing fraction of features that would be included in the final model. These analyses also identified which of the classification algorithms yielded the best performing final model. The final mortality prediction model was then built on the entire original training set (development set + validation set) using the chosen classification algorithm applied to the selected features and then evaluated on the holdout test set using the 6 evaluation metrics.