Immunity-based genetic algorithm for classification rule discovery

被引：0

作者：

Wang, ZQ ^{[1
]}

Zhang, DX ^{[1
]}

机构：

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

来源：

ADVANCES IN NATURAL COMPUTATION, PT 2, PROCEEDINGS | 2005年 / 3611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：

Immune algorithm is a global optimal algorithms based on the biological immune theory. In this paper, a novel immune algorithm is proposed for classification rule discovery. The idea of immunity is mainly realized through two steps based on reasonably selecting vaccines, i.e., a vaccination and an immune selection. Experimental results show that immune algorithm performs better than RISE with respect to predictive accuracy and rule list mined simplicity.

引用

页码：727 / 734

页数：8

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