Paper Title:
A Clustering Method Based on Attribute Reduction and SOM
  Abstract

In Insurance industry, data redundancy is an extremely common problem in the population statistics. As a result a satisfactory clustering quality can rarely be obtained with the traditional clustering method. To handle this kind of problems a clustering model based on attributes reduction and SOM neural network was proposed. Using attributes reduction rules redundant information can be easily distinguished and essential attributes effectively located. And therefore the clustering quality can also be improved evidently. Experiments conducted in the H life insurance company show the method can cope with the problems mentioned above effectively.

  Info
Periodical
Edited by
Qi Luo
Pages
1001-1006
DOI
10.4028/www.scientific.net/AMM.58-60.1001
Citation
Y. Q. Zheng, S. N. Yu, P. M. Jiang, "A Clustering Method Based on Attribute Reduction and SOM", Applied Mechanics and Materials, Vols. 58-60, pp. 1001-1006, 2011
Online since
June 2011
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