Empirical Investigation on COVID-19 Cases Using Machine Learning Approach: State Wise Analysis of India

9 Pages Posted: 22 Jul 2021

See all articles by Chiransh Singh Mehra

Chiransh Singh Mehra

JIMS Engineering Management Technical Campus

Ruchi Agarwal

JIMS Engineering Management Technical Campus

Kalpana Jha

JIMS Engineering Management Technical Campus

Date Written: May 10, 2021

Abstract

This COVID-19 pandemic gives the opportunities to scientists for their big researches and covid-19 become as a challenge for scientific communities to foster their Researches and Development activities. This paper presents a comparative analysis of machine learning model to predict the COVID-19 outbreaks. We analyze the most affected states which the helps of line graphs and show the number of deaths, number of recoveries and total number of confirmed cases of that states This paper builds the predictive models that can predict the upcoming number of confirmed cases, upcoming number of deaths and future recoveries for next 90 days with the higher accuracy We used several machine learning algorithms including linear regression, Random Forest, Decision Tree and ARIMA model for forecasting. analyze the most affected states which the helps of line graphs and show the number of deaths, number of recoveries and total number of confirmed cases of that states.

Note: Funding Statement: No financial support for this study.

Declaration of Interests: No conflicts of interest.

Keywords: Covid-19, Future Prediction, State wise Analysis, Random Forest

Suggested Citation

Mehra, Chiransh Singh and Agarwal, Ruchi and Jha, Kalpana, Empirical Investigation on COVID-19 Cases Using Machine Learning Approach: State Wise Analysis of India (May 10, 2021). Proceedings of the International Conference on Innovative Computing & Communication (ICICC) 2021, Available at SSRN: https://ssrn.com/abstract=3842815 or http://dx.doi.org/10.2139/ssrn.3842815

Chiransh Singh Mehra (Contact Author)

JIMS Engineering Management Technical Campus ( email )

Ruchi Agarwal

JIMS Engineering Management Technical Campus ( email )

Kalpana Jha

JIMS Engineering Management Technical Campus ( email )

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