Selected article for: "linear regression and polynomial regression"

Author: Agarwal, S.; Bansal, H.
Title: Methodical Analysis and Prediction of COVID-19 Cases of China and SAARC Countries
  • Cord-id: upgqph0n
  • Document date: 2021_1_1
  • ID: upgqph0n
    Snippet: COVID-19 pandemic has become a major challenge for all the countries of the world. No medicine has been developed till now to cure it. Coronavirus (COVID-19) is the family of viruses that causes illness and has symptoms like the common cold, influenza, and severe acute respiratory syndrome (SARS) that spread via breathing droplets. Proper analysis and prediction of the COVID-19 patients and its increasing rate of spread will help the government and people to mitigate its effect. This gives a rea
    Document: COVID-19 pandemic has become a major challenge for all the countries of the world. No medicine has been developed till now to cure it. Coronavirus (COVID-19) is the family of viruses that causes illness and has symptoms like the common cold, influenza, and severe acute respiratory syndrome (SARS) that spread via breathing droplets. Proper analysis and prediction of the COVID-19 patients and its increasing rate of spread will help the government and people to mitigate its effect. This gives a reason to analyze, compare, and predict the cases in India, China, and SAARC countries to make early decision for taking preventive measures to combat its effects in a timely manner. In this paper, we have analyzed COVID-19 cases from January 21, 2020 to June 25, 2020 and have predicted the cases of COVID-19 for the period of next two weeks using multiple linear regression and polynomial regression models of machine learning. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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