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

Rachana Yadav1 , Amit Kumar Manjhwar2

Section:Research Paper, Product Type: Journal Paper
Volume-10 , Issue-5 , Page no. 65-73, May-2022

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v10i5.6573

Online published on May 31, 2022

Copyright © Rachana Yadav, Amit Kumar Manjhwar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Rachana Yadav, Amit Kumar Manjhwar, “Data Based Model for Predicting COVID-19 Incidence Using Data Mining,” International Journal of Computer Sciences and Engineering, Vol.10, Issue.5, pp.65-73, 2022.

MLA Style Citation: Rachana Yadav, Amit Kumar Manjhwar "Data Based Model for Predicting COVID-19 Incidence Using Data Mining." International Journal of Computer Sciences and Engineering 10.5 (2022): 65-73.

APA Style Citation: Rachana Yadav, Amit Kumar Manjhwar, (2022). Data Based Model for Predicting COVID-19 Incidence Using Data Mining. International Journal of Computer Sciences and Engineering, 10(5), 65-73.

BibTex Style Citation:
@article{Yadav_2022,
author = {Rachana Yadav, Amit Kumar Manjhwar},
title = {Data Based Model for Predicting COVID-19 Incidence Using Data Mining},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2022},
volume = {10},
Issue = {5},
month = {5},
year = {2022},
issn = {2347-2693},
pages = {65-73},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5470},
doi = {https://doi.org/10.26438/ijcse/v10i5.6573}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v10i5.6573}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5470
TI - Data Based Model for Predicting COVID-19 Incidence Using Data Mining
T2 - International Journal of Computer Sciences and Engineering
AU - Rachana Yadav, Amit Kumar Manjhwar
PY - 2022
DA - 2022/05/31
PB - IJCSE, Indore, INDIA
SP - 65-73
IS - 5
VL - 10
SN - 2347-2693
ER -

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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.

Key-Words / Index Term

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

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