• Bogdan Gliwa AGH University of Science and Technology
  • Aleksander Byrski AGH University of Science and Technology




Neuro-fuzzy classifier, NEFCLASS, neural networks, fuzzy systems


The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which wasmodified. The presented classifier was compared to popular classifiers – neural networks andk-nearest neighbours. Efficiency of modifications in classifier was compared with methodsused in original model NEFCLASS (learning methods). Accuracy of classifier was testedusing 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin.Moreover, influence of ensemble classification methods on classification accuracy waspresented.


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Author Biographies

Bogdan Gliwa, AGH University of Science and Technology

Faculty of Electrical Engineering, Automatics,IT and Electronics, Department of Computer Science

Aleksander Byrski, AGH University of Science and Technology

Faculty of Electrical Engineering, Automatics,IT and Electronics, Department of Computer Science


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How to Cite

Gliwa, B., & Byrski, A. (2013). HYBRID NEURO-FUZZY CLASSIFIER BASED ON NEFCLASS MODEL. Computer Science, 12, 115. https://doi.org/10.7494/csci.2011.12.0.115




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