A PSO-Based classification rule mining algorithm

被引：0

作者：

Wang, Ziqiang ^{[1
]}

Sun, Xia ^{[1
]}

Zhang, Dexian ^{[1
]}

机构：

[1] Henan Univ Technol, Sch Informat Sci & Engn, Zhengzhou 450052, Peoples R China

来源：

ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, PROCEEDINGS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE | 2007年 / 4682卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Classification rule mining is one of the important problems in the emerging field of data mining which is aimed at finding a small pp set of rules from the training data set with predetermined targets. To efficiently mine the classification rule from databases, a novel classification rule mining algorithm based on particle swarm optimization (PSO) was proposed. The experimental results show that the proposed algorithm achieved higher predictive accuracy and much smaller rule list than other classification algorithm.

引用

页码：377 / 384

页数：8

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