Data Based Model for Predicting COVID-19 Incidence Using Data Mining

Authors

  • Yadav R Computer Science and Engineering, M.I.T.S. Gwalior, India
  • Kumar Manjhwar A Computer Science and Engineering, M.I.T.S. Gwalior, India

DOI:

https://doi.org/10.26438/ijcse/v10i5.6573

Keywords:

Covid19, Machine Learning, , EDA (Exploratory data analysis), Linear Regression,, Gaussian Naïve Baye, Decision Tree,, Ensemble learning,, Random forest,, Gradient boosting

Abstract

Since, covid19 is affecting many countries in the world therefore, to take the necessary steps in order to control the outbreak or incidence of covid19, which is possible if we know the outbreak or incidence of covid19 which is possible with machine learning. Therefore, in this study we are analyzing the covid19 data of India and performing EDA (exploratory data analysis) and proposing various machine learning algorithm in order to predict the outbreak of covid19. We are using various machine learning algorithms like Linear regression, Gaussian naïve bayes, Decision tree and ensemble learning like random forest, gradient boosting and then finding the best algorithm by comparing their accuracy score. With the help of best algorithm, the outbreak of covid19 to manage the health crisis in each country can be controlled by taking the essential steps.

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Published

2022-05-31
CITATION
DOI: 10.26438/ijcse/v10i5.6573
Published: 2022-05-31

How to Cite

[1]
R. Yadav and A. Kumar Manjhwar, “Data Based Model for Predicting COVID-19 Incidence Using Data Mining”, Int. J. Comp. Sci. Eng., vol. 10, no. 5, pp. 65–73, May 2022.

Issue

Vol. 10 No. 5 (2022): IJCSE May Edition

Section

Research Article

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