Attribute Reduction of Rough Sets in Mining Market Value Functions

Authors:
Jiajin Huang;Chunnian Liu;Chuangxin Ou;Y. Y. Yao;Ning Zhong
Affiliations:
-;-;-;-;-
Venue:
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
Year:
2003

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Abstract

The linear model of market value functions is a new method for direct marketing. Just like other methods in direct marketing, attribute reduction is very important to deal with large databases. In the paper, we apply the algorithm of attribute reduction, which is based on the combination of rough set theory with the Boosting algorithm, to the linear model of market value functions. Experimental results compared with the ELSA/ANN model show that the proposed algorithms can be used effectively in the linear model of market value functions.