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...
- 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