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A feature selection technique for generation of classification committees and its application to categorization of laryngeal images
Department of Applied Electronics, Kaunas University of Technology, Lithuania .
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0003-2185-8973
Department of Applied Electronics, Kaunas University of Technology, Lithuania .
Department of Applied Electronics, Kaunas University of Technology, Lithuania .
2009 (English)In: Pattern Recognition, ISSN 0031-3203, E-ISSN 1873-5142, Vol. 42, no 5, p. 645-654Article in journal (Refereed) Published
Abstract [en]

This paper is concerned with a two phase procedure to select salient features (variables) for classification committees. Both filter and wrapper approaches to feature selection are combined in this work. In the first phase, definitely redundant features are eliminated based on the paired t-test. The test compares the saliency of the candidate and the noise features. In the second phase, the genetic search is employed. The search integrates the steps of training, aggregation of committee members, selection of hyper-parameters, and selection of salient features into the same learning process. A small number of genetic iterations needed to find a solution is the characteristic feature of the genetic search procedure developed. The experimental tests performed on five real-world problems have shown that significant improvements in Classification accuracy can be obtained in a small number of iterations if compared to the case of using all the features available.

Place, publisher, year, edition, pages
New York: Pergamon Press, 2009. Vol. 42, no 5, p. 645-654
Keywords [en]
Feedfoward neural networks, Feature subset-selection, Support vector machine, Evolutionary ensembles, Negative correlation, Genetic algorithms, Classifiers, Recognition, Accuracy, Systems
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:hh:diva-100DOI: 10.1016/j.patcog.2008.08.025ISI: 000263431200006Scopus ID: 2-s2.0-58249093836OAI: oai:DiVA.org:hh-100DiVA, id: diva2:235710
Available from: 2009-09-17 Created: 2009-09-17 Last updated: 2018-01-13Bibliographically approved

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Verikas, Antanas

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • vancouver
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  • de-DE
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  • Other locale
More languages
Output format
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