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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      1 Jan 2023, Volume 38 Issue 1   
    Article

    1. FUTURE PREDICTION IN COVID-19 BASED ON VARIABLE SELECTION WITH THE SUPPORT OF DATA MINING AND MACHINE LEARNING
    N. Sankar 1 and S. Manikandan 2
    Journal of Data Acquisition and Processing, 2023, 38 (1): 3712-3724 . 

    Abstract

    Novel Coronavirus is an infection caused by SARS CoV 2 that began in China in 2019. The data mining is the important and dedicated tools for forecasting the hidden knowledge with the help of pre-existing dataset. The covid analysis and vaticination for consider different affiliated parameters like name of the sates (countries), total affected cases, cases in particular date, active cases, discharged cases, discharged cases in particular date, overall death, and deaths in particular date. In this paper was aimed at tracing the suitable variable selection for future prediction and subsequently based on suitable variable to predict the future trends related to total cases admitted and total cases discharged on expected date using overall total cases. Similarly predict discharged cases using total cases admitted in India. Numerical illustrations also give to prove the results and conclusions using regression model and its accuracy parameters.

    Keyword

    Covid-19, Data Mining, Regression model, coefficient of determination and prediction


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ISSN 1004-9037

         

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