An Approach to Feature Selection Based on Ant Colony Optimization and Rough Set

被引：0
|
作者：
Wu, Junyun [1 ]
Qiu, Taorong [1 ]
Wang, Lu [1 ]
Huang, Haiquan [1 ]
机构：
[1] Nanchang Univ, Dept Comp, Nanchang 330031, Jiangxi, Peoples R China
来源：
INTELLIGENT COMPUTING AND INFORMATION SCIENCE, PT I | 2011年 / 134卷 / 0I期
关键词：
Feature selection; Ant colony optimization algorithm; Rough set;
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：
Feature selection plays an important role in many fields. This paper proposes a method for feature selection which combined the rough set method and ant colony optimization algorithm. The algorithm used the attribute dependence and the attribute importance as the inspiration factor which applied to the transfer rules. For further, the quality of classification based on rough set method and the length of the feature subset were used to build the pheromone update strategy. Through the test of data set, results show that the proposed method is feasible.
引用
收藏
页码：466 / 471
页数：6
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