基于k -均值算法的上市公司聚类应用

Y. Qian
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引用次数: 1

摘要

信贷市场中存在着众多的客户,需要对其进行分类。提出了基于历史财务比率的K-means算法,利用聚类分析技术对浙江省上市企业进行分析。分析了与财务属性相关的一些指标,选择了9个财务指标。根据对上市公司更好的估值,我们采用“试错法”,选择4个作为聚类数量。81个样本分为两组:一个训练组有60家公司,另一个测试组有21家公司。测试结果表明,所训练的模型可用于浙江省上市公司的聚类
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An Application Based on K-Means Algorithm for Clustering Companies Listed
There exist many customers in credit market that needs to be classified into distinct groups. K-means algorithm are presented, which based on the historical financial ratios, utilizing the cluster analysis technology to analyze the listed enterprises in Zhejiang province. Some indicators related to financial attributes are analyzed, and nine finance indicators are chosen. According to better valuation on the companies listed, we apply to "try and error" and choose 4 as the number of clustering. 81 samples are divided into two groups: one training group with 60 firms and other testing group with 21 samples. Testing results shows that the model trained can be available for clustering companies listed in Zhejiang province
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