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Selecting neural networks for making a committee decision
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0003-2185-8973
Kaunas University of Technology, Department of Applied Electronics, Studentu 50, 3031, Kaunas, Lithuania.ORCID iD: 0000-0002-5686-0646
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
2002 (English)In: ARTIFICIAL NEURAL NETWORKS - ICANN 2002 / [ed] Dorronsoro, J R, Berlin: Springer Berlin/Heidelberg, 2002, Vol. 2415, p. 420-425Conference paper, Published paper (Refereed)
Abstract [en]

To improve recognition results, decisions of multiple neural networks can be aggregated into a committee decision. In contrast to the ordinary approach of utilizing all neural networks available to make a committee decision, we propose creating adaptive committees, which are specific for each input data point. A prediction network is used to identify classification neural networks to be fused for making a committee decision about a given input data point. The jth output value of the prediction network expresses the expectation level that the jth classification neural network will make a correct decision about the class label of a given input data point. The effectiveness of the approach is demonstrated on two artificial and three real data sets.

Place, publisher, year, edition, pages
Berlin: Springer Berlin/Heidelberg, 2002. Vol. 2415, p. 420-425
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 2415
Keywords [en]
Neural networks
National Category
Bioinformatics (Computational Biology) Telecommunications Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:hh:diva-35788DOI: 10.1007/3-540-46084-5_68ISI: 000181441900068Scopus ID: 2-s2.0-33745928507ISBN: 978-3-540-44074-1 (print)ISBN: 978-3-540-46084-8 (electronic)OAI: oai:DiVA.org:hh-35788DiVA, id: diva2:1195561
Conference
12th International Conference on Artifical Neural Networks (ICANN 2002), AUG 28-30, 2002, MADRID, SPAIN
Available from: 2018-04-05 Created: 2018-04-05 Last updated: 2018-04-05Bibliographically approved

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Verikas, AntanasMalmqvist, Kerstin

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Verikas, AntanasLipnickas, ArunasMalmqvist, Kerstin
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CAISR - Center for Applied Intelligent Systems ResearchHalmstad Embedded and Intelligent Systems Research (EIS)
Bioinformatics (Computational Biology)TelecommunicationsBioinformatics and Systems Biology

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf