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A machine learning methodology for forecasting of the COVID-19 cases in India

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preprint
posted on 17.04.2020 by R. Sujatha, Jyotir Chatterjee, Aboul ella Hassanien
Here, we propose a basic model that could be helpful to foresee the spread of COVID-2019. We performed linear regression, Multilayer perceptron and Vector autoregression model for expectation on the COVID-19 kaggle information to anticipate the epidemiological pattern of the disease and rate of COVID-2019 cases in India. Predicted the possible trends of COVID-19 impacts in India based on data collected from Kaggle. With the prevailing data about confirmed, recovered and death across India for over the time duration helps in predicting and forecasting the near future. For additional examination or future point of view, case definition and information assortment must be kept up continuously.

Funding

Not Applicable

History

Email Address of Submitting Author

jyotirchatterjee@gmail.com

ORCID of Submitting Author

0000-0003-2527-916X

Submitting Author's Institution

Lord Buddha Education Foundation

Submitting Author's Country

Nepal

Licence

Exports