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Advances in Fuzzy Systems
Volume 2012 (2012), Article ID 984325, 10 pages
Research Article

Fuzzy One-Class Classification Model Using Contamination Neighborhoods

Department of Control, Automation and System Analysis, St. Petersburg State Forest Technical University, Institutski per. 5, St. Petersburg 194021, Russia

Received 8 April 2012; Accepted 16 August 2012

Academic Editor: M. Onder Efe

Copyright © 2012 Lev V. Utkin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A fuzzy classification model is studied in the paper. It is based on the contaminated (robust) model which produces fuzzy expected risk measures characterizing classification errors. Optimal classification parameters of the models are derived by minimizing the fuzzy expected risk. It is shown that an algorithm for computing the classification parameters is reduced to a set of standard support vector machine tasks with weighted data points. Experimental results with synthetic data illustrate the proposed fuzzy model.