Feature selection for classification using an ant colony system

被引：11

作者：

Abd-Alsabour N. ^{[1
]}

Randall M. ^{[1
]}

机构：

[1] School of Information Technology, Bond University, QLD

来源：

Proceedings - 6th IEEE International Conference on e-Science Workshops, e-ScienceW 2010 | 2010年

关键词：

Ant colony optimisation; Feature selection;

D O I：

10.1109/eScienceW.2010.23

中图分类号：

学科分类号：

摘要：

Many applications such as pattern recognition require selecting a subset of the input features in order to represent the whole set of features. The aim of feature selection is to remove irrelevant or redundant features while keeping the most informative ones. In this paper, an ant colony system approach for solving feature selection for classification is presented. The proposed algorithm was tested using artificial and real-world datasets. The results are promising in terms of the accuracy of the classifier and the number of selected features in all the used datasets. The results of the proposed algorithm have been compared with other results available in the literature and found to be favorable. © 2010 IEEE.

引用

页码：86 / 91

页数：5

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