hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
Using Unlabelled Data to Train a Multilayer Perceptron
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS). Kaunas University of Technology, Kaunas, Lithuania.ORCID iD: 0000-0003-2185-8973
Kaunas University of Technology, Kaunas, Lithuania.ORCID iD: 0000-0002-0415-1434
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
Kaunas University of Technology, Kaunas, Lithuania.
2001 (English)In: Advances in Pattern Recognition — ICAPR 2001: Second International Conference Rio de Janeiro, Brazil, March 11–14, 2001 Proceedings / [ed] Sameer Singh, Nabeel Murshed, Walter Kropatsch, Heidelberg: Springer Berlin/Heidelberg, 2001, Vol. 2013, p. 40-49Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents an approach to using both labelled and unlabelled data to train a multilayer perceptron. The unlabelled data are iteratively pre-processed by a perceptron being trained to obtain the soft class label estimates. It is demonstrated that substantial gains in classification performance may be achieved from the use of the approach when the labelled data do not represent adequately the entire class distributions. The experimental investigations performed have shown that the approach proposed may be successfully used to train neural networks for learning different classification problems. © Springer-Verlag Berlin Heidelberg 2001.

Place, publisher, year, edition, pages
Heidelberg: Springer Berlin/Heidelberg, 2001. Vol. 2013, p. 40-49
Series
Lecture Notes in Computer Science, ISSN 0302-9743
Keywords [en]
Classification (of information), Multilayers, Neural networks, Pattern recognition, Class distributions, Class labels, Classification performance, Experimental investigations, Unlabelled data, Multilayer neural networks
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:hh:diva-40869DOI: 10.1007/3-540-44732-6_5Scopus ID: 2-s2.0-0005977561ISBN: 978-3-540-41767-5 (print)OAI: oai:DiVA.org:hh-40869DiVA, id: diva2:1392758
Conference
Conference of 2nd International Conference on Advances in Pattern Recognition (ICAPR 2001), Rio de Janeiro, Brazil, March 11-14, 2001
Available from: 2020-02-10 Created: 2020-02-10 Last updated: 2020-02-10

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Verikas, AntanasMalmqvist, Kerstin

Search in DiVA

By author/editor
Verikas, AntanasGelzinis, AdasMalmqvist, Kerstin
By organisation
Halmstad Embedded and Intelligent Systems Research (EIS)
Other Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 4 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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