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Forecasting Prediction of Covid-19 Outbreak Using Linear Regression

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Data Intelligence and Cognitive Informatics

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

Coronavirus these days becomes an alarming topic as the loss of lives is increasing every day. Coronavirus was born in China (Wuhan) and has spread globally within no time. Machine learning is used to forecast the future outcomes almost in all areas like computers, medical, business, security, and many more. In this study, various machine learning techniques such as Linear Regression, SVM, Random Forest, Logistic Regression, and KNN are used to forecast the future tendency of SARS-CoV-2. The polynomial feature with degree 3 is used to enhance the accuracy of the model. Dataset is collected from Johns Hopkins University dashboard. It contains 3 separate files of Covid-19 such as confirmed case, recovered case, and death case dataset. This article has four phases, i.e., data preprocessing, data classification, training, testing, and parametric evaluation such as RMSE, MSE, MAE, and R2-score. In this study, Linear Regression (LR) shows excellent outcome in contrast to other approaches. LR has a minimum mean squared error value and an obtained accuracy of 99.92% for Covid-19 confirmed cases, 99.73% for recovered cases, and 99.60% for death cases. Results show that if humans become unsocial and the administration imposes strict lockdown, there is a great chance to overcome this disease within a small period.

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Authors and Affiliations

  1. Computer Engineering and Technology, Guru Nanak Dev University, Amritsar, India

    Gurleen Kaur & Prabhpreet Kaur

  2. Guru Nanak Dev University, Amritsar, Punjab, India

    Parminder Kaur

  3. Department of Computer Science, Guru Nanak Dev University, Amritsar, Punjab, India

    Navinderjit Kaur

Authors
  1. Gurleen Kaur
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  2. Parminder Kaur
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  3. Navinderjit Kaur
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  4. Prabhpreet Kaur
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Corresponding author

Correspondence to Gurleen Kaur .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, GITAM University, Bangalore, Karnataka, India

    I. Jeena Jacob

  2. Department of Mathematics and Computer Science, Ashland University, River Forest, IL, USA

    Selvanayaki Kolandapalayam Shanmugam

  3. Department of Artificial Intelligence, Lviv Polytechnic National University, Lviv, Ukraine

    Ivan Izonin

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Kaur, G., Kaur, P., Kaur, N., Kaur, P. (2023). Forecasting Prediction of Covid-19 Outbreak Using Linear Regression. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Izonin, I. (eds) Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-6004-8_17

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