Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6885
Title: Increasing accuracy of two-class pattern recognition with enhanced fuzzy functions
Authors: Çelikyılmaz, Aslı
Türkşen, İsmail Burhan
Aktaş, Ramazan
Doğanay, M. Mete
Ceylan, N. Başak
Keywords: Fuzzy classification
Improved fuzzy clustering
Fuzzy Functions
Data mining
Early warning system
Decision support systems
Issue Date: 2009
Publisher: Pergamon-Elsevier Science Ltd
Abstract: In building an approximate fuzzy classifier system, significant effort is laid oil estimation and fine tuning of fuzzy sets. However, in such systems little thought is given to the way in which membership functions are combined within fuzzy rules. In this paper, a robust method, improved fuzzy classifier functions (IFCF) design is proposed for two-class pattern recognition problems. A supervised hybrid improved fuzzy Clustering for classification (IFC-C) algorithm is implemented for structure identification. IFC-C algorithm is based oil it dual optimization method, which yields simultaneous estimates of the parameters of (c-classification functions together with fuzzy c partitioning of dataset based oil a distance measure. The merit of novel IFCF is that the information oil natural grouping of data samples i.e., the membership values, are utilized as additional predictors of each fuzzy classifier function to improve accuracy of system model. Improved fuzzy classifier functions are approximated using statistical and soft computing approaches. A new semi-non-parametric inference mechanism is implemented for reasoning. The experimental results Of the new modeling approach indicate that the new IFCF is it promising method for two-class pattern recognition problems. (c) 2007 Elsevier Ltd. All rights reserved.
URI: https://doi.org/10.1016/j.eswa.2007.11.039
https://hdl.handle.net/20.500.11851/6885
ISSN: 0957-4174
1873-6793
Appears in Collections:İşletme Bölümü / Department of Management
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record

CORE Recommender

SCOPUSTM   
Citations

22
checked on Sep 23, 2022

WEB OF SCIENCETM
Citations

19
checked on Sep 24, 2022

Page view(s)

32
checked on Dec 26, 2022

Google ScholarTM

Check

Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.