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COMPARISON OF MACHINE LEARNING ALGORITHMS FOR PREDICTING MORTALITY FROM COVID-19 VIRUS

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Date
2022
Author
Doroshenko, Iryna
Knihnitska, Tatiana
Deretorska, Tetiana
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Abstract
The article compares the effectiveness of Machine Learning Algorithms on the example of Covid-19 distribution data. The following Machine Learning algorithms are considered: Logistic Regression, Support Vector Machine, Random Forest, K-Means. The accuracy of the constructed models was used to compare the Algorithms. All statistical studies were conducted in the R Programming language
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https://archer.chnu.edu.ua/xmlui/handle/123456789/5927
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