@inproceedings{77fdc6fdb2b9466e9cc8af1f605e5df1,
title = "Experimental comparison of feature subset selection using G A and AGO algorithm",
abstract = "Practical pattern classification and knowledge discovery problems require selecting a useful subset of features from a much larger set to represent the patterns to be classified. Exhaustive evaluation of possible feature subsets is usually infeasible in practice because of the large amount of computational effort required. Bio-inspired algorithms offer an attractive approach to find near-optimal solutions to such optimization problems. This paper presents an approach to feature subset selection using bioinspired algorithms. Our experiments with several benchmark real-world pattern classification problems demonstrate the feasibility of this approach to feature subset selection in the automated design of neural networks for pattern classification and knowledge discovery.",
author = "Keunjoon Lee and Jinu Joo and Jihoon Yang and Vasant Honavar",
year = "2006",
doi = "10.1007/11811305_51",
language = "English (US)",
isbn = "3540370250",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "465--472",
editor = "Xue Li and Za{\"i}ane, {Osmar R.} and Zhanhuai Li",
booktitle = "Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings",
address = "Germany",
note = "2nd International Conference on Advanced Data Mining and Applications, ADMA 2006 ; Conference date: 14-08-2006 Through 16-08-2006",
}