Covid-19 Risk Prediction Using Machine Learning Techniques

Authors

  • Ms. M. Angel   PG Student, Department of CSE , VV College Of Engineering, Tirunelveli, Tamil Nadu, India
  • Dr. S. Ebenezer Juliet  Associate Professor, Department of CSE, VV College Of Engineering, Tirunelveli, Tamil Nadu, India

Keywords:

COVID-19, Support vector machine, Linear Regression, Machine learning Techniques

Abstract

Nowadays Machine Learning (ML) Techniques are used for accurate COVID-19 risk prediction. Several prediction methods are being popularly used to handle forecasting problems. In this paper the capability of ML models to forecast the number of upcoming patients affected by COVID-19 is presented because COVID-19 is considered as a potential threat to mankind. Various risk prediction factors of COVID-19 which performs well in forecasting the new confirmed cases, death rate as well as recovery rate are identified. Two standard forecasting models, such as Support vector Machine,(SVM) and Linear Regression(LR) have been used for prediction to forecast the threatening factors of COVID-19. The results produced by the above techniques proved it a promising prediction mechanism for the current scenario of the COVID-19 pandemic. Also the experimental results proved that the SVM performs better than Linear Regression.

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International Journal of Scientific Research in Science and Technology

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Published

2021-04-10

Issue

Volume 9, Issue 1, March-April-2021

Section

Research Articles

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How to Cite

[1]
Ms. M. Angel , Dr. S. Ebenezer Juliet, " Covid-19 Risk Prediction Using Machine Learning Techniques, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 9, Issue 1, pp.86-93, March-April-2021.