Skip to main content
Presentation
Feature selection for classification using an ant colony system
e-Science 2010: Sixth IEEE international conference on e-Science
  • Nadia Abd-Alsabour, Bond University
  • Marcus Randall, Bond University
Date of this Version
12-7-2010
Document Type
Conference Paper
Publication Details

Published Version.

Abd-Alsabour, N. & Randall, M. (2010). Feature selection for classification using an ant colony system. Paper presented at the Sixth IEEE international conference on e-Science: e-Science 2010, Brisbane, Australia.

Access the conference website.

2010 HERDC submission. FoR Code: 080500

© Copyright IEEE, 2010. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

ISBN
978-0-7695-4295-9
Disciplines
Abstract
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 rising 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.
Citation Information
Nadia Abd-Alsabour and Marcus Randall. "Feature selection for classification using an ant colony system" e-Science 2010: Sixth IEEE international conference on e-Science (2010) p. 86 - 91
Available at: http://works.bepress.com/marcus_randall/33/