COVID-19 RECOVERY CASES PREDICTION USING MACHINE LEARNING

Abstract

Coronavirus or COVID-19 is a relatively new pandemic gravely affecting the globe. All around the globe people are getting infected by it. Unfortunately a large number of patients who are elderly or immune-compromised die after contracting the virus. In this paper, we aim to test many machine learning techniques and algorithms in order topredict the number of people successfully recovering after contracting the deadly virus. And that prediction is made on a day to day basis. We implemented Random Forest Regression model for an accurate prediction. This study will accurately predict the number of recovered patients on a day to day basis. Thus, we can see a lot of probable uses for this study in the future sense.