COVID-19 Future Forecasting Using Machine Learning
| Author(s) | : | Rutuja Satpute, Dhanashree Bobade, Prof. Amruta Kapre |
| Institution | : | Shubhamkaroti Rawalekar Amarsingh Jamadar |
| Published In | : | Vol. 8, Issue 5 — May 2021 |
| Page No. | : | 18-22 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
predictions on behaviour after the surgery, which studies have shown, both with and without control, to be moreeffective when using models and without a human subject bias (ML). In several applications where adverse risk variableswere observed and priority was given to machine learning models. Various methods of prediction are also used to deal withprediction issues. This study shows the ability to estimate the number of COVID-9 patients who, via a machine learningmodel, are seen as a possible threat to humanity. For COVID-19 threatening factors prediction four typical predictionmodels were used: linear regression (LR), LORSO, vector aid (SVM), and exponential blending (ES). The number of newpatients affected, the number of deaths, and the number of recoveries are three ways to estimate for 10 days in each of themodels
Rutuja Satpute, Dhanashree Bobade, Prof. Amruta Kapre, “COVID-19 Future Forecasting Using Machine Learning”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 8, Issue 5, pp. 18-22, May 2021.
