Analysis On the Progression of COVID with the Impact of Climatic Conditions

Abstract

Globally since December 2019 Coronavirus disease (COVID- 19) has been identified as a potentially severe contagious disease and WHO has declared the spread of COVID-19 as pandemic. Hence, Study of COVID-19 is most essential for prevention and proper treatment of the disease. COVID is a contagious disease in mammals and birds. In humans, coronavirus causes respiratory track infections that can be mild, such as some cases of the common cold, and the others can be lethal, such as SARS, MERS and COVID-19. Machine learning is a powerful technique which is used to train computer programs involving big data to take automated decisions. It is proposed to develop an efficient machine learning algorithm for analysis of progression of COVID-19 with the impact of climatic conditions such as temperature rainfall and humidity. Feature selection has several objectives such as enhancing model performance by avoiding overfitting in the case of supervised classification. Thus EDA is performed for a large set of data that is fed for different algorithms in order to arrive at efficient and lesser RMSE values.