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
收藏
页码：727 / 734
页数：8
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