Machine learning and dengue forecasting: comparing random forests and artificial neural networks for predicting dengue burden at national and sub-national scales in Colombia

The robust estimate and forecast capability of random forests (RF) has been widely recognized, however this ensemble machine learning method has not been widely used in mosquito- borne disease forecasting. In this study, two sets of RF models were developed at the national (pooled department-level d...

Full description

Autores:
Zhao, Naizhuo
Charland, Katia
Carabali, Mabel
Nsoesie, Elaine
Maheu-Giroux, Mathieu
Rees, Erin
Yuan, Mengru
Garcia, Cesar
Jaramillo Ramírez, Gloria Isabel
Zinser, Kate
Tipo de recurso:
Article of investigation
Fecha de publicación:
2020
Institución:
Universidad Cooperativa de Colombia
Repositorio:
Repositorio UCC
Idioma:
OAI Identifier:
oai:repository.ucc.edu.co:20.500.12494/32758
Acceso en línea:
https://hdl.handle.net/20.500.12494/32758
Palabra clave:
Arbovirus
Prediction
Network
Arbovirus
Prediction
Network
Rights
openAccess
License
Atribución – No comercial – Sin Derivar