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Selecting neural networks for a committee decision
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.
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
2002 (English)In: International Journal of Neural Systems, ISSN 0129-0657, E-ISSN 1793-6462, Vol. 12, no 5, p. 351-361Article in journal (Refereed) Published
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 proposed technique is tested in three aggregation schemes, namely majority vote, averaging, and aggregation by the median rule and compared with the ordinary neural networks fusion approach. The effectiveness of the approach is demonstrated on two artificial and three real data sets.

Place, publisher, year, edition, pages
Singapore: World Scientific, 2002. Vol. 12, no 5, p. 351-361
Keywords [en]
Artificial Intelligence, Computer Simulation, Neural Networks (Computer), Neural network committee, Decision fusion, Neural network selection
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hh:diva-3541DOI: 10.1142/S0129065702001229PubMedID: 12424806Scopus ID: 2-s2.0-2342502764OAI: oai:DiVA.org:hh-3541DiVA, id: diva2:285853
Available from: 2010-01-13 Created: 2009-12-01 Last updated: 2018-01-12Bibliographically approved

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Verikas, Antanas

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CiteExportLink to record
Permanent link

Direct link
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