Letters: A neuro-fuzzy approach for diagnosis of antibody deficiency syndrome

Authors:
Joon Shik Lim;Dianhui Wang;Yong-Soo Kim;Sudhir Gupta
Affiliations:
Software College, Kyungwon University, Seongnam, Gyeonggi-Do 405-760, South Korea;Department of Computer Science and Computer Engineering, La Trobe University, Melbourne, VIC 3086, Australia;Software College, Kyungwon University, Seongnam, Gyeonggi-Do 405-760, South Korea;Department of Medicine, University of California, Irvine, CA 92868, USA
Venue:
Neurocomputing
Year:
2006

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Abstract

This paper presents a neuro-fuzzy approach for diagnosis of antibody deficiency syndrome, where a new neuro-fuzzy network with fuzzy activation functions (FAFs) at hidden layer is used. The FAFs capturing some essential information on pattern distributions, can be adaptively constructed using training examples. To improve the generalization capability and reduce the model complexity, a heuristic method for feature selection is proposed by measuring the size of non-overlapped areas of the FAFs. The effectiveness of our proposed techniques is investigated by an immunology clinical data set collected from the University of California, Irvine (UCI) immunology laboratory.