Benchmarking missing-values approaches for predictive models on health databases
Benchmarking missing-values approaches for predictive models on health databases
Abstract Background As databases grow larger, it becomes harder to fully control their collection, and they frequently come with missing values. These large databases are well suited to train machine learning models, e.g., for forecasting or to extract biomarkers in biomedical settings. Such predictive approaches can use discriminativeā€”rather than generativeā€”modeling ā€¦