Feature Selection using Ant Colony Optimization

被引：0
|
作者：
Deriche, Mohamed [1 ]
机构：
[1] King Fahd Univ Petr & Minerals, Dept Elect Engn, Dhahran 31261, Saudi Arabia
来源：
2009 6TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS AND DEVICES, VOLS 1 AND 2 | 2009年
关键词：
Feature selection; ant systems; ant colony optimization; local measure;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The ant feature selection algorithm has recently been proposed as a new method for feature subset selection. It uses measures of both local feature importance and overall performance of subsets to search the feature space for optimal solutions. In this paper, we evaluate the effect of different local importance measures; namely the Fisher Criterion, the Mutual Information based Feature Selection, and the Mutual Information Evaluation Function.
引用
收藏
页码：619 / 622
页数：4
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