{"title":"社会经济和健康指标的比较聚类和可视化:肯尼亚案例","authors":"Evans Kiptoo Korir","doi":"10.1016/j.seps.2024.101961","DOIUrl":null,"url":null,"abstract":"<div><p>In this study, we used principal component analysis (PCA) to reduce the dimensionality of the data and used a hierarchical and K-means clustering technique to stratify counties in Kenya into five clusters. The grouped counties were then projected onto a geographic map to understand the relationship between their location and socioeconomic and health indicators. The results obtained may be useful to the county and state governments in future plans to promote inclusive and sustainable economic development.</p></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":null,"pages":null},"PeriodicalIF":6.2000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0038012124001605/pdfft?md5=b7f233352ca2f5390c4e04903ef306de&pid=1-s2.0-S0038012124001605-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Comparative clustering and visualization of socioeconomic and health indicators: A case of Kenya\",\"authors\":\"Evans Kiptoo Korir\",\"doi\":\"10.1016/j.seps.2024.101961\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this study, we used principal component analysis (PCA) to reduce the dimensionality of the data and used a hierarchical and K-means clustering technique to stratify counties in Kenya into five clusters. The grouped counties were then projected onto a geographic map to understand the relationship between their location and socioeconomic and health indicators. The results obtained may be useful to the county and state governments in future plans to promote inclusive and sustainable economic development.</p></div>\",\"PeriodicalId\":22033,\"journal\":{\"name\":\"Socio-economic Planning Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2024-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0038012124001605/pdfft?md5=b7f233352ca2f5390c4e04903ef306de&pid=1-s2.0-S0038012124001605-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Socio-economic Planning Sciences\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0038012124001605\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Socio-economic Planning Sciences","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0038012124001605","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
摘要
在这项研究中,我们使用了主成分分析法(PCA)来降低数据的维度,并使用分层和 K 均值聚类技术将肯尼亚的县划分为五个群组。然后将分组后的县投影到地理图上,以了解其位置与社会经济和健康指标之间的关系。所获得的结果可能对县和州政府未来促进包容性和可持续经济发展的计划有所帮助。
Comparative clustering and visualization of socioeconomic and health indicators: A case of Kenya
In this study, we used principal component analysis (PCA) to reduce the dimensionality of the data and used a hierarchical and K-means clustering technique to stratify counties in Kenya into five clusters. The grouped counties were then projected onto a geographic map to understand the relationship between their location and socioeconomic and health indicators. The results obtained may be useful to the county and state governments in future plans to promote inclusive and sustainable economic development.
期刊介绍:
Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry.
Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution.
Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.