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A Novel Fuzzy Rule-Based Classification System Based on Classifier Selection Strategy

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2 Author(s)
Kardan, N. ; Dept. of Comput. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran ; Minaei-Bidgoli, B.

Fuzzy systems have been used as a mechanism to build classifiers which are called fuzzy rule based classification systems (FRBCSs). In this paper, a new method for improving this kind of classifiers, based on ensemble strategy, is proposed. Here instead of building a classifier or a fusion of a group of them, we build some base classifiers and select one for every test pattern. A number of UCI datasets are used to assess the performance of the proposed method in comparison with reward and punishment and another method. Simulation results show our method's performance is a notch above these schemas.

Published in:

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Date of Conference:

11-13 Dec. 2009