Identification of Patterns in CO<sub>2</sub> Emissions among 208 Countries: K-Means Clustering Combined with PCA and Non-Linear <i>t</i>-SNE Visualization

Identification of Patterns in CO<sub>2</sub> Emissions among 208 Countries: K-Means Clustering Combined with PCA and Non-Linear <i>t</i>-SNE Visualization

This paper identifies patterns in total and per capita CO<sub>2</sub> emissions among 208 countries considering different emission sources, such as cement, flaring, gas, oil, and coal. This research uses linear and non-linear dimensional reduction techniques, combining K-means clustering...

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Bibliographic Details
Main Authors: Ana Lorena Jiménez-Preciado, Salvador Cruz-Aké, Francisco Venegas-Martínez
Format: Article
Language:English
Published: MDPI AG 2024-08-01
Series:Mathematics
Subjects:
CO<sub>2</sub> emissions
K-means clustering
principal component analysis
<i>t</i>-SNE
Online Access:https://www.mdpi.com/2227-7390/12/16/2591

Internet

https://www.mdpi.com/2227-7390/12/16/2591

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