Marketing audit value model based on rough set and support vector regression machine

被引:0
作者
Che Cheng [1 ]
Ao Shan [1 ]
Tang Shoulian [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Beijing, Beijing, Peoples R China
来源
FIRST INTERNATIONAL WORKSHOP ON KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS | 2007年
关键词
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study applies a new model based on rough set and support vector regression machine to enterprises' marketing audit value. To improve the efficiency, rough set was used to reduce the number of indexes. To improve the precision, the support vector regression machine was used. Then, the marketing audit value data of several companies were analyzed and 21 main indexes of marketing audit value were used. The experimental results demonstrate that the new method based on rough set and support vector regression machine has better precision than artificial neural network method and is more efficient than pure support vector regression machine method.
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收藏
页码:201 / 204
页数:4
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