| 胡纯严,胡良平.无序样品聚类分析——基于欧氏和最短距离法[J].四川精神卫生杂志,2024,37(S1):48-53.Hu Chunyan,Hu Liangping,Cluster analysis of disordered samples： based on the methods of Euclidean distance and the minimum distance[J].SICHUAN MENTAL HEALTH,2024,37(S1):48-53 |
| 无序样品聚类分析——基于欧氏和最短距离法 |
| Cluster analysis of disordered samples： based on the methods of Euclidean distance and the minimum distance |
| 投稿时间：2024-01-10 |
| DOI：10.11886/scjsws20240110002 |
| 中文关键词: 无序样品 欧氏距离 最短距离 聚类分析 树形图 |
| 英文关键词:Disordered samples Euclidean distance Minimum distance Cluster analysis Dendrogram |
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| 中文摘要: |
| 本文目的是介绍与无序样品聚类分析有关的基本概念、计算方法、两个实例以及使用SAS实现计算的方法。基本概念包括无序样品与有序样品、影响距离计算的要素、并类规则、谱系聚类及其两个步骤、聚类资料与分类资料的区别；计算方法涉及闵科夫斯基距离（含欧氏距离）计算公式和最短距离计算公式；两个实例分别是“我国27个少数民族16岁男孩身体形态学数据”和“1995年我国14个省、直辖市的劳动卫生监督数据”；借助SAS软件，对两个实例的数据进行了无序样品聚类分析，并对SAS输出结果做出了解释。 |
| 英文摘要: |
| The purpose of this article was to introduce the basic concepts， calculation methods， two examples and the calculation methods using SAS related to the cluster analysis of disordered samples. Basic concepts included disordered samples and ordered samples， factors affecting distance calculation， clustering rules， hierarchical clustering and its two steps， and the difference between the clustering data and the classification data. The calculation methods involved the Minkowski distance （including Euclidean distance） calculation formula and the minimum distance calculation formula. The data in the two examples were "body morphological data of 16-year-old boys from 27 ethnic minorities in China" and "labor health supervision data of 14 provinces and municipalities in China in 1995". With the help of SAS software， cluster analysis of disordered samples was performed on the data in the two examples， and the explanation of the SAS output results was given. |
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