Kernel-based machine learning models for the prediction of dengue and chikungunya morbidity in Colombia

Dengue and Chikungunya fever are two viral diseases of great public health concern in Colombia and other tropical countries as they are both transmitted by Aedes mosquitoes, which are endemic to this area. In recent years, there have been unprecedented outbreaks of these infections. Therefore, the d...

Full description

Autores:

Tipo de recurso:

Fecha de publicación:

2017

Institución:

Universidad Tecnológica de Bolívar

Repositorio:

Repositorio Institucional UTB

Idioma:

eng

OAI Identifier:

oai:repositorio.utb.edu.co:20.500.12585/8960

Acceso en línea:

https://hdl.handle.net/20.500.12585/8960

Palabra clave:

Chikungunya
Dengue
Forecasting
Gaussian processes
Kernel ridge regression
Machine learning
Artificial intelligence
Diseases
Forecasting
Gaussian distribution
Gaussian noise (electronic)
Health
Learning systems
Public health
Regression analysis
Chikungunya
Dengue
Gaussian processes
Kernel ridge regressions
Machine learning models
Mean absolute percentage error
Research and development
Time series forecasting
Learning algorithms

Rights

restrictedAccess

License

http://creativecommons.org/licenses/by-nc-nd/4.0/