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Predictor output sensitivity and feature similarity-based feature selection
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, LT-51368 Kaunas, Lithuania.
Department of Applied Electronics, Kaunas University of Technology, LT-51368 Kaunas, Lithuania.
Department of Applied Electronics, Kaunas University of Technology, LT-51368 Kaunas, Lithuania.
2008 (English)In: Fuzzy sets and systems (Print), ISSN 0165-0114, E-ISSN 1872-6801, Vol. 159, no 4, p. 422-434Article in journal (Refereed) Published
Abstract [en]

This paper is concerned with a feature selection technique capable of generating an efficient feature set in a few selection steps. The feature saliency measure proposed is based on two factors, namely, the fuzzy derivative of the predictor output with respect to the feature and the similarity between the feature being considered and the feature set. The use of the fuzzy derivative enables modelling the vagueness that occurs in estimating the predictor output sensitivity. The feature similarity measure employed allows avoiding utilization of very redundant features. The experimental investigations performed on five real world problems have shown the effectiveness of the feature selection technique proposed. The technique developed removed a large number of features from the original data sets without reducing the classification accuracy of a classifier. In contrast, the accuracy of the classifiers utilizing the reduced feature sets was higher than those exploiting all the original features.

Place, publisher, year, edition, pages
Elsevier, 2008. Vol. 159, no 4, p. 422-434
Keywords [en]
Classification, Design, Measurement, Performance
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-1324DOI: 10.1016/j.fss.2007.05.020ISI: 000253476300004Scopus ID: 2-s2.0-37349087901Local ID: 2082/1703OAI: oai:DiVA.org:hh-1324DiVA, id: diva2:238542
Available from: 2008-04-16 Created: 2008-04-16 Last updated: 2017-12-13Bibliographically 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
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
  • text
  • asciidoc
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