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Prediction of Corona Virus Outbreak using Machine Learning
2021 IEEE International Conference on Intelligent Systems, Smart and Green Technologies, ICISSGT 2021 ; : 42-47, 2021.
Article in English | Scopus | ID: covidwho-1788709
ABSTRACT
Predicting the corona virus can be divided into several phases, including a state-wide analysis that includes active, confirmed, cured, deaths as well as an increase in cases on a daily basis that includes each and every state of India as well as Union Territories. This also includes a thread of new corona virus cases from throughout India and forecasts the outbreak's conclusion in the next days. Machine learning algorithms like SVM, Linear Regression and Decision Tree Regression are used to analyze this data and improve this model's outcome. In this study, Jupyter notebook is used which provides an environment that is suited for machine learning principles. This technique provides for a comprehensive analysis of the virus's spread, including total and active cases, as well as forecasting future outbreaks and a weekly study epidemic. © 2021 IEEE
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: 2021 IEEE International Conference on Intelligent Systems, Smart and Green Technologies, ICISSGT 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: 2021 IEEE International Conference on Intelligent Systems, Smart and Green Technologies, ICISSGT 2021 Year: 2021 Document Type: Article