Malaria Risk Prediction Using Machine Learning in Lamwo District

Abstract

comparison of bayesian belief network and random forest in malaria risk prediction in lamwo district analyzing weighing the impact of the climatic and non climatic factors on the high levels of malaria spread in malaria risk prediction and it was found out that bayesian belief network predicts malaria risk better than the random forest