A Clustering Method Based on Attribute Reduction and SOM

Abstract:

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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 et al., "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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Price:

$35.00

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