Identifying the Most Relevant Attributes to Explain Peaks of COVID-19 Infections and Deaths by Machine Learning Methods-Reference-Cited by-同舟云学术

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Identifying the Most Relevant Attributes to Explain Peaks of COVID-19 Infections and Deaths by Machine Learning Methods

Published:2023 Issue:1 Volume:15 Page:1-9
ISSN:1793-8201
Container-title:International Journal of Computer Theory and Engineering
language:
Short-container-title:IJCTE

Author:

Pena Gabriel,Gambini Juliana,Barraza Nestor R.

Publisher

IACSIT Press

Subject

Computational Theory and Mathematics,Computer Science Applications

Link

http://www.ijcte.org/vol15/IJCTE-V15N1-1326.pdf

Reference99 articles.

1. [1] N. R. Barraza, G. Pena, and V. Moreno, "A non-homogeneous

2. Markov early epidemic growth dynamics model. Application

3. to the SARS-CoV-2 pandemic," Chaos, Solitons & Fractals,

4. vol. 139, p. 110297, 2020. [Online]. Available: http://www.

5. sciencedirect.com/science/article/pii/S0960077920306937

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