基于K-Means算法的Covid-19全球大流行聚类分析

Bakti Siregar, Jurusan Statistika, Universitas Matana
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引用次数: 0

摘要

像Covid-19这样的大流行是世界上有史以来最大的现实问题之一。这个案例证实了不确定性是如何影响全球经济的。Covid-19大流行不可能在世界范围内用一种方法解决,这取决于病例的严重程度。因此,本研究旨在使用K-means算法对Covid-19的严重程度进行聚类,以反映全球经济状况,数据来源为“我们的数据世界”。这一研究结果可以作为材料,通过参考一个集群中所列国家的政策和战略来克服全球大流行的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis Clustering of the Global Pandemic Covid-19 using K-Means Algorithm
A pandemic such as Covid-19 is one of the biggest real problems ever in the world. This case has confirmed how uncertainty affects the global economy. The pandemic Covid-19 cannot be solved by one method over the world, it depends on the severity of the case. Therefore, this research aims to cluster the severity of Covid-19 using the K-means algorithm to reflect the global economic conditions using data sources from "Our World in Data". The results of this research can be used as materials to overcome the impact of the global pandemic by referring to policies and strategies from a country that is indicated in one cluster.
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