An application based on K-means algorithm for clustering companies listed

被引：0
|
作者：
Ye Qian [1 ]
机构：
[1] Zhejiang Univ Finance & Econ, Sch Finance, Hangzhou, Peoples R China
来源：
2006 IEEE INTERNATIONAL CONFERENCE ON SERVICE OPERATIONS AND LOGISTICS, AND INFORMATICS (SOLI 2006), PROCEEDINGS | 2006年
关键词：
clustering analysis; financial ratios; K-Means Algorithm; listed companies;
D O I：
10.1109/SOLI.2006.235231
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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.
引用
收藏
页码：723 / 727
页数：5
相关论文
共 50 条
  • [1] K-means algorithm and its application for clustering companies listed in Zhejiang province
    Qian, Y.
    [J]. DATA MINING VII: DATA, TEXT AND WEB MINING AND THEIR BUSINESS APPLICATIONS, 2006, 37 : 35 - 44
  • [2] The Application of K-Means Clustering Algorithm Based on Hadoop
    Zhong, Yurong
    Liu, Dan
    [J]. PROCEEDINGS OF 2016 IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYSIS (ICCCBDA 2016), 2016, : 88 - 92
  • [3] An Improved K-means Algorithm and Its Application for Assessment of Culture Industry Listed Companies
    Sun, Haibo
    Wang, Limin
    Han, Xuming
    [J]. FOURTEENTH WUHAN INTERNATIONAL CONFERENCE ON E-BUSINESS, 2015, : 132 - 136
  • [4] A k-means based clustering algorithm
    Bloisi, Domenico Daniele
    Locchi, Luca
    [J]. COMPUTER VISION SYSTEMS, PROCEEDINGS, 2008, 5008 : 109 - 118
  • [5] A K-means Clustering Algorithm Based on Similarity Coefficient and Application
    Wu Xiangting
    Lu Yan
    Gao Zhaozi
    [J]. COMPREHENSIVE EVALUATION OF ECONOMY AND SOCIETY WITH STATISTICAL SCIENCE, 2009, : 1031 - 1035
  • [6] Improvement Study and Application Based on K-Means Clustering Algorithm
    Luo, Yu
    Yu, Li
    Liu, Xing-hua
    [J]. FUZZY INFORMATION AND ENGINEERING, VOLUME 2, 2009, 62 : 937 - +
  • [7] The Improvement and Application of a K-Means Clustering Algorithm
    Tao, Li Jun
    Hong, Liu Yin
    Yan, Hao
    [J]. PROCEEDINGS OF 2016 IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYSIS (ICCCBDA 2016), 2016, : 93 - 96
  • [8] Research on k-means Clustering Algorithm An Improved k-means Clustering Algorithm
    Shi Na
    Liu Xumin
    Guan Yong
    [J]. 2010 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY AND SECURITY INFORMATICS (IITSI 2010), 2010, : 63 - 67
  • [9] Design and application of a text clustering algorithm based on parallelized k-means clustering
    Wang, Hui
    Zhou, Chengdong
    Li, Leixiao
    [J]. Revue d'Intelligence Artificielle, 2019, 33 (06) : 453 - 460
  • [10] A Clustering Method Based on K-Means Algorithm
    Li, Youguo
    Wu, Haiyan
    [J]. INTERNATIONAL CONFERENCE ON SOLID STATE DEVICES AND MATERIALS SCIENCE, 2012, 25 : 1104 - 1109
12345