THERMAL SCIENCE

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Randa Alharbi

MODELING AND CLASSIFICATION OF DEATHS DUE TO COVID 19 BASED ON MACHINE LEARNING TECHNIQUE

ABSTRACT
Statistical classification is recently considered one of the most important and most common methods in machine learning models and consists of building models that define the target of research interest. There are many classification methods that can be used to predict the value of a response. In this article, we are interested in machine learning applications to classify the new deaths due to Covid-19. Under consideration BIC criterion, the experimental results have shown that the E (Equal variance) with four is the best mixture model. The convergence in the algorithm of expectation-maximization is satisfied after 167 iterations. The World Health Organization has presented the source of data over the period of March 2, 2020 to August 5, 2020.
KEYWORDS
Expectation-Maximization algorithm, Machine learning Modeling, classification, Gaussian mixtures model, prediction
PAPER SUBMITTED: 2022-10-15
PAPER REVISED: 2022-11-20
PAPER ACCEPTED: 2022-11-26
PUBLISHED ONLINE: 2023-01-07
DOI REFERENCE: https://doi.org/10.2298/TSCI221015196A
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2023, VOLUME 27, ISSUE Issue 1, PAGES [405 - 410]
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Modeling and classification of deaths due to Covid 19 based on machine learning technique

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence