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Advances in Fuzzy Systems
Volume 2016 (2016), Article ID 7173054, 11 pages
Research Article

A Similarity Classifier with Bonferroni Mean Operators

1Laboratory of Applied Mathematics, Lappeenranta University of Technology, P.O. Box 20, 53851 Lappeenranta, Finland
2Department of Mathematics, Makerere University, P.O. Box 7062, Kampala, Uganda
3School of Business and Management, Lappeenranta University of Technology, P.O. Box 20, 53851 Lappeenranta, Finland

Received 29 March 2016; Accepted 22 June 2016

Academic Editor: Katsuhiro Honda

Copyright © 2016 Onesfole Kurama et al. 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 similarity classifier based on Bonferroni mean based operators is introduced. The new Bonferroni mean based variant of the similarity classifier is also extended to cover a new Bonferroni-OWA variant. The new Bonferroni-OWA based similarity classifier raises the question of how to accomplish the weighting needed and for this reason we also examine a number of linguistic quantifiers for weight generation. The new proposed similarity classifier variants are tested on four real world medical research related data sets. The results are compared with results from two previously presented similarity classifiers, one based on the generalized mean and another based on an arithmetic mean operator. The results show that comparatively better classification accuracy can be reached with the proposed new similarity classifier variants.