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| 无序样品聚类分析——熵值法 |
| Cluster analysis of disordered samples: entropy value method |
| 投稿时间：2024-06-03 修订日期：2024-06-03 |
| DOI： |
| 中文关键词: 熵 信息熵 差异系数 同趋势化 归一化 聚类分析 |
| 英文关键词:Entropy Information Entropy Diversity coefficient Synchronization Normalization Cluster analysis |
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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。基本概念包括熵、信息熵、同趋势化与归一化、熵值与差异系数、权重系数；计算方法涉及计算原理和熵值法的计算公式；两个实例中分别为“东南大学附属中大医院1990年—1999年住院医疗质量指标的调查结果”以及“15个高新园区自主创新能力相关指标的调查结果”；借助SAS对两个实例的数据进行了无序样品聚类分析，基于最优分割法给出了分档的结果，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, computational methods, two examples and their implementation with SAS related to cluster analysis of disordered samples. The basic concepts included entropy, information entropy, synchronization and normalization, entropy value and diversity coefficient, weight coefficient. The calculation method involved the principle of calculation and the formula of entropy value method. The data in the two examples were respectively "the survey results of inpatient healthcare quality indicators of Zhongda Hospital Affiliated to Southeast University from 1990 to 1999" and "the survey results of independent innovation ability indicators of 15 high-tech parks". Using SAS software, the data in the two examples were analyzed by cluster analysis of disordered samples, and the results of classification were given based on the optimal segmentation method, and the output results of SAS were explained. |
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