Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Engineering Applications of Artificial Intelligence
Design of adaptive fuzzy model for classification problem
Engineering Applications of Artificial Intelligence
How good are fuzzy If-Then classifiers?
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Nonsingleton fuzzy logic systems: theory and application
IEEE Transactions on Fuzzy Systems
Implementation of evolutionary fuzzy systems
IEEE Transactions on Fuzzy Systems
The shape of fuzzy sets in adaptive function approximation
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Combining multiple views: Case studies on protein and arrhythmia features
Engineering Applications of Artificial Intelligence
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This paper aims at analyzing a non-singleton fuzzy logic classifier (NSFLC) and assessing its ability to cope with uncertainties in pattern classification problems. The analysis demonstrate that the NSFLC has fuzzy classification boundary and noise suppression capability. These characteristics means that the NSFLC is particulary suitable for problems where the boundaries between classes is non-distinct. To further demonstrate the benefits offered by a NSFLC, a non-singleton fuzzy logic classifier evolved using Genetic Algorithm (GA) is assessed using a benchmark cardiac arrhythmias classification problem. Results indicate that a NSFLC achieved good classification accuracy using features that are easier to extract, but contain more uncertainties.