Predicating & Forecasting of Coronavirus Disease 2019 (COVID-19) using Machine Learning Approach

Abstract

By extensive researches on the Machine Learning or ML, it has been established that they would play an important role in future to correctly predict the prognostic values of different decisions during operative procedures. This will hence help in decision making. These Machine Learning models are not new. They have been used previously in many of the application areas which required to identify and rank different unfavorable components for a danger. To deal with the different forecasting issues, there are many different famous prediction techniques under employment. This research is also based on the efficiency of such Machine Learning or ML models. It shows what these models are capable of in regard to correctly predicting the total number of patients suffering from the disease that is posing serious threats to mankind, i.e. corona virus disease 2019. Specifically, we use four predicting Machine Learning models to predict the endangering models of corona virus disease 2019. These models include the support vector machine (SVM), least absolute shrinkage and selection operator (LASSO), exponential smoothing (ES) and the linear regression (LR).