Use of Classification Techniques for the Analysis of Data Related to COVID-19 in México.

Ivan Rael Núñez-Harper,Bogart Yail Márquez,Arnulfo Alanis

ARTIIS (1)(2022)

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摘要
SARS-CoV-2 has bought many challenges to the world, socially, economically, and healthy habits. Even to those that have not experienced the sickness itself, and even though it has changed the lifestyle of the people across the world nation wise the effects of COVID-19 need to be analyzed and understood, analyzing a large amount of data is a process by itself, in this document details the analysis of the data collected from Mexico by the Secretary of Health, the data was analyzed by implementing statistics, and classification methods known as K-Means, C&R Tree and TwoStep Cluster, using processed and unprocessed data. With the main emphasis on K-means. The study has the purpose of detecting what makes the highest impact on a person, to get sick, and succumb to the effects of the disease. In the study, it was found that in Mexico the age of risk is at its highest at the age of 57, and the ones at the highest risk of mortality are those with hypertension and obesity, with those that present both at the age of 57 having a 19.37% of death.
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关键词
SARS-CoV-2,COVID-19,K-Means,C&R Tree,Clustering,Data classification,TwoStep Cluster
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