Machine Learning for Analyzing Non-Countermeasure Factors Affecting Early Spread of COVID-19

Machine Learning for Analyzing Non-Countermeasure Factors Affecting Early Spread of COVID-19

The COVID-19 pandemic affected the whole world, but not all countries were impacted equally. This opens the question of what factors can explain the initial faster spread in some countries compared to others. Many such factors are overshadowed by the effect of the countermeasures, so we studied the...

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Bibliographic Details
Main Authors: Vito Janko, Gašper Slapničar, Erik Dovgan, Nina Reščič, Tine Kolenik, Martin Gjoreski, Maj Smerkol, Matjaž Gams, Mitja Luštrek
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:International Journal of Environmental Research and Public Health
Subjects:
COVID-19
machine learning
feature significance
feature correlation
risk factors
Online Access:https://www.mdpi.com/1660-4601/18/13/6750

Internet

https://www.mdpi.com/1660-4601/18/13/6750

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