Identifying Similar Groups of Countries According to the Impact of Corona Virus (COVID-19) by a Two-Layer Clustering Method

Juan Riofrío, Carlos Muñoz-Moncayo, Isidro R. Amaro, Israel Pineda

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

This paper presents a new clustering algorithm to identify groups of countries. First, a layer of several clustering methods is applied to the original dataset. Then, after performing dimensionality reduction techniques like t-SNE or SOM on the resulting data, a second clustering layer (K-Means) is applied to identify the final clusters. This method is applied to a dataset from 163 countries, considering the following variables population, area, Gross Domestic Product (GDP), Gross Domestic Product adjusted for Purchase Power Parity (GDP-PPP), and COVID-19 related data (Confirmed, Recovered, and Deaths). The implementation with SOM dimensionality reduction outperformed the one with t-SNE for the considered dataset. We expect that using this information, countries can have an insight on which measures against COVID-19 replicate or avoid, based on the results in countries from the same cluster.

Idioma originalInglés
Título de la publicación alojadaArtificial Intelligence, Computer and Software Engineering Advances - Proceedings of the CIT 2020
EditoresMiguel Botto-Tobar, Henry Cruz, Angela Díaz Cadena
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas34-48
Número de páginas15
ISBN (versión impresa)9783030680794
DOI
EstadoPublicada - 2021
Publicado de forma externa
Evento15th Multidisciplinary International Congress on Science and Technology, CIT 2020 - Quito, Ecuador
Duración: 26 oct. 202030 oct. 2020

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen1326 AISC
ISSN (versión impresa)2194-5357
ISSN (versión digital)2194-5365

Conferencia

Conferencia15th Multidisciplinary International Congress on Science and Technology, CIT 2020
País/TerritorioEcuador
CiudadQuito
Período26/10/2030/10/20

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