Incorporating dynamic uncertainties into a fuzzy classifier
Autor(en): | Hülsmann, J. Buschermöhle, A. Brockmann, W. |
Stichwörter: | Benchmarking; Classification process; Computer circuits; Dynamic uncertainty; Fuzzy classifier; Fuzzy classifiers; Fuzzy logic; Fuzzy sets; Trust management; Uncertain features; Uncertain informations; Uncertainty; Uncertainty analysis, Benchmark datasets; Uncertainty, Classification (of information) | Erscheinungsdatum: | 2011 | Herausgeber: | Atlantis Press | Journal: | Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2011 and French Days on Fuzzy Logic and Applications, LFA 2011 | Volumen: | 1 | Ausgabe: | 1 | Startseite: | 388 | Seitenende: | 395 | Zusammenfassung: | Dealing with classification problems in practice often has to cope with uncertain information, either in the training or in the operation phase or both. Modeling these uncertainties allows to enhance the robustness or performance of the classifier. In this paper we focus on the operation phase and present a general, but simple extension to rule based fuzzy classifier to do so. Therefor uncertain features are gradually and dimension wise faded out of the classification process. An artificial two-dimensional dataset is used to visualize the effectiveness of this approach. Investigations on three benchmark datasets shows the performance and gain in robustness. © 2011. The authors-Published by Atlantis Press. |
Beschreibung: | Conference of Joint 7th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2011 and 17th French Days on Fuzzy Logic and Applications, LFA 2011 ; Conference Date: 18 July 2011 Through 18 July 2011; Conference Code:94762 |
ISBN: | 9789078677000 | DOI: | 10.2991/eusflat.2011.4 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867586733&doi=10.2991%2feusflat.2011.4&partnerID=40&md5=76d9889b629f211b415c01d1739cb2dc |
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geprüft am 17.05.2024