Abdu Gumaei1,2,*, Mabrook Al-Rakhami1, Mohamad Mahmoud Al Rahhal3, Fahad Raddah H. Albogamy3, Eslam Al Maghayreh3, Hussain AlSalman1
CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 315-329, 2021, DOI:10.32604/cmc.2020.012045
- 30 October 2020
Abstract The fast spread of coronavirus disease (COVID-19) caused by SARSCoV-2 has become a pandemic and a serious threat to the world. As of May 30,
2020, this disease had infected more than 6 million people globally, with hundreds
of thousands of deaths. Therefore, there is an urgent need to predict confirmed cases
so as to analyze the impact of COVID-19 and practice readiness in healthcare systems.
This study uses gradient boosting regression (GBR) to build a trained model to predict
the daily total confirmed cases of COVID-19. The GBR method can minimize the loss
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