COVID-19 Case Prediction: Regression and Machine Learning Models

In this video, we discuss how to design statistical regression and machine learning models to predict the number of COVID-19 (coronavirus) cases in countries across the world. To this end, we design a regression based ensemble learning model consisting of Linear regression, Ridge, Lasso, ARIMA, and SVR that takes the previous 14 days data into account to predict the number of new COVID-19 cases in the short-term. The ensemble model outputs the best performance by taking into account the performance of all the models. We consider data from top 50 countries around the world that have the highest number of confirmed cases between January 21, 2020 and April 30, 2020. Our results in terms of relative percentage error show that the ensemble method provides superior prediction performance for a vast majority of these countries with less than 10% error for 6 countries and less than 40% error for 27 countries. Paper: http://find.cs.binghamton.edu/paper/COVID-prediction.pdf Code: https://bitbucket.org/rrausha1/covid-19-case-prediction/src/master/ Johns Hopkins Github:https://github.com/CSSEGISandData/COVID-19 -------------------------------------------------------------------------------------------------------------------- This channel is part of CSEdu4All, an educational initiative that aims to make computer science education accessible to all! We believe that everyone has the right to good education, and geographical and political boundaries should not be a barrier to obtaining knowledge and information. We hope that you will join and support us in this endeavor! --------- Help us spread computer science knowledge to everyone around the world! Please support the channel and CSEdu4All by hitting "LIKE" and the "SUBSCRIBE" button. Your support encourages us to create more accessible computer science educational content. Patreon: https://www.patreon.com/csedu4all GoFundMe: https://www.gofundme.com/f/csedu4all --------- Find more interesting courses and videos in our website Website: https://csedu4all.org/ --------- Find and Connect with us on Social Media: Facebook: https://www.facebook.com/csedu4all Twitter: https://twitter.com/SeetharamAnand LinkedIn: https://www.linkedin.com/in/anand-seetharam-5444775a/