Comparing support vector regression and random forests for predicting malaria incidence in Mozambique


Accurate prediction of malaria incidence is essential for the management of several activities in the ministry of health in Mozambique. This study investigates the comparison of support vector machines (SVMs) and random forests (RFs) for this purpose. A dataset with records of malaria cases covering the period 1999-2008 was used to evaluate predictive… (More)


3 Figures and Tables