Experimental comparison of feature subset selection using G A and AGO algorithm

Keunjoon Lee, Jinu Joo, Jihoon Yang, Vasant Honavar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

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.

Original languageEnglish (US)
Title of host publicationAdvanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings
EditorsZhanhuai Li, Xue Li, Osmar R. Zaïane
PublisherSpringer Verlag
Pages465-472
Number of pages8
ISBN (Electronic)9783540370253
ISBN (Print)3540370250, 9783540370253
StatePublished - Jan 1 2006
Event2nd International Conference on Advanced Data Mining and Applications, ADMA 2006 - Xi'an, China
Duration: Aug 14 2006Aug 16 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4093 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Conference on Advanced Data Mining and Applications, ADMA 2006
CountryChina
CityXi'an
Period8/14/068/16/06

Fingerprint

Feature Subset Selection
Pattern Classification
Set theory
Pattern recognition
Knowledge Discovery
Data mining
Subset
Large Set
Classification Problems
Optimal Solution
Neural Networks
Benchmark
Optimization Problem
Neural networks
Evaluation
Demonstrate
Experiment
Experiments

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Lee, K., Joo, J., Yang, J., & Honavar, V. (2006). Experimental comparison of feature subset selection using G A and AGO algorithm. In Z. Li, X. Li, & O. R. Zaïane (Eds.), Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings (pp. 465-472). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4093 LNAI). Springer Verlag.
Lee, Keunjoon ; Joo, Jinu ; Yang, Jihoon ; Honavar, Vasant. / Experimental comparison of feature subset selection using G A and AGO algorithm. Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings. editor / Zhanhuai Li ; Xue Li ; Osmar R. Zaïane. Springer Verlag, 2006. pp. 465-472 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Lee, K, Joo, J, Yang, J & Honavar, V 2006, Experimental comparison of feature subset selection using G A and AGO algorithm. in Z Li, X Li & OR Zaïane (eds), Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4093 LNAI, Springer Verlag, pp. 465-472, 2nd International Conference on Advanced Data Mining and Applications, ADMA 2006, Xi'an, China, 8/14/06.

Experimental comparison of feature subset selection using G A and AGO algorithm. / Lee, Keunjoon; Joo, Jinu; Yang, Jihoon; Honavar, Vasant.

Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings. ed. / Zhanhuai Li; Xue Li; Osmar R. Zaïane. Springer Verlag, 2006. p. 465-472 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4093 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Lee K, Joo J, Yang J, Honavar V. Experimental comparison of feature subset selection using G A and AGO algorithm. In Li Z, Li X, Zaïane OR, editors, Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings. Springer Verlag. 2006. p. 465-472. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).