Computational Intelligence and Healthcare Informatics

11COVID-19: Classification of Countries for Analysis and Prediction of Global Novel Corona Virus Infections Disease Using Data Mining Techniques

Sachin Kamley¹*, Shailesh Jaloree², R.S. Thakur³ and Kapil Saxena⁴

¹Department of Computer Applications, S.AT.I., Vidisha, India

²Department of Applied Math’s and Science, S.AT.I., Vidisha, India

³Department of Computer Applications, M.A.N.I.T., Bhopal, India

⁴Department of Computer Science and Applications, Career College, Bhopal, India

Abstract

For the couple of days, Novel Corona Virus Infection Disease (COVID-19) pandemic has become a major challenge as well as threat to the society. Presently, more than 170 countries are infected from this virus including India. However, no medicines and antidote have been made at present to cure this disease. Preventing these infections to large community level immediate actions are required. In this way, data mining has capability to handle data quickly and effectively tracking and controlling the spread of virus infections. In this study, global dataset of 204 countries for the period of 31 January to 19 May from Worldometer website are considered for study purpose and data from 20 May to 8 June is considered to predict the evaluation of the outbreak, i.e., 3 weeks ahead. Three most prominent data mining techniques like Linear Regression (LR), Association Rule Mining (ARM), and Back Propagation Neural Network (BPNN) are utilized to predict and analyze the COVID-19 dataset. Finally, BPNN and ...