Machine learning and dengue forecasting: Comparing random forests and artificial neural networks for predicting dengue burdens at the national sub-national scale in Colombia
N. Zhao, K. Charland, M. Carabali, E. Nsoesie, M. Maher-Giroux, E. Rees, M. Yuan, C. Garcia Balaguera, G. Jaramillo Ramirez, K. Zinszer
This paper compares random forests and artificial neural networks for predicting dengue cases in Colombia, finding that random forests provide more accurate forecasts, especially when applied nationally to local data.
bioRxiv · Jan 14, 2020Immunology