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Leverages Based Neural Networks Fusion
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0003-2185-8973
Kaunas University of Technology, Lithuania.
Kaunas University of Technology, Lithuania.
2004 (English)In: Neural information processing, 2004, p. 446-451Conference paper, Published paper (Refereed)
Abstract [en]

To improve estimation results, outputs of multiple neural networks can be aggregated into a committee output. In this paper, we study the usefulness of the leverages based information for creating accurate neural network committees. Based on the approximate leave-one-out error and the suggested, generalization error based, diversity test, accurate and diverse networks are selected and fused into a committee using data dependent aggregation weights. Four data dependent aggregation schemes – based on local variance, covariance, Choquet integral, and the generalized Choquet integral – are investigated. The effectiveness of the approaches is tested on one artificial and three real world data sets.

Place, publisher, year, edition, pages
2004. p. 446-451
Series
Lecture notes in computer science, ISSN 0302-9745 ; 3316
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hh:diva-3324DOI: 10.1007/978-3-540-30499-9_68ISI: 000225878300068Scopus ID: 2-s2.0-33846929995OAI: oai:DiVA.org:hh-3324DiVA, id: diva2:300225
Conference
11th International Conference, ICONIP 2004, Calcutta
Available from: 2010-02-25 Created: 2009-12-01 Last updated: 2018-01-12Bibliographically approved

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Verikas, Antanas

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CiteExportLink to record
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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