Predicting cases in India using Machine Learning: COVID-19

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

Predicting cases in India using Machine Learning: COVID-19
Author(s):
Payal Patel, Mehul P. Barot
Keywords:
COVID-19, Masking, Pandemic Waves, SARS-CoV2, Vaccination.
Abstract
COVID-19, a virus that is said to have originated in Wuhan, China, has a genuine effect on almost the entire world's population. The Health Organization (WHO) has called it a global pandemic due to the complications that this particular health epidemic has created all over the world. Because of continual alterations in the virus's genetic components, the pandemic has returned in numerous waves. Here, we are detecting the COVID-19 cases, i.e., confirmed, death, and cured cases in India only. We are performing this analysis based on the cases occurring in different states of India in chronological dates. On this dataset, first, we performed data cleansing and feature selection, then performed forecasting of all classes using linear regression model and support vector machine, where support vector machine model outperformed the other, therefore, the linear regression model is used for prediction and analysis of all the results. The predicted value of the model is compared with actual result to find the accuracy.
Article Details
Unique Paper ID: 154924 Publication Volume & Issue: Volume 8, Issue 12 Page(s): 845 - 854
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