A data-driven interpretable ensemble framework based on tree models for forecasting the occurrence of COVID-19 in the USA

This prevalence of coronavirus disease 2019 (COVID-19) has become one of the most serious public health crises. Tree-based machine learning methods, with the advantages of high efficiency, and strong interpretability, have been widely used in predicting diseases. A data-driven interpretable ensemble...

Descripción completa

Detalles Bibliográficos
Autores principales: Zheng, Hu-Li, An, Shu-Yi, Qiao, Bao-Jun, Guan, Peng, Huang, De-Sheng, Wu, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9492466/
https://www.ncbi.nlm.nih.gov/pubmed/36131178
http://dx.doi.org/10.1007/s11356-022-23132-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9492466/
https://www.ncbi.nlm.nih.gov/pubmed/36131178
http://dx.doi.org/10.1007/s11356-022-23132-3

Ejemplares similares