DOI: https://doi.org/10.15588/1607-3274-2016-2-9
FUZZY CLASSIFIER LEARNING BASED ON DISTANCE BETWEEN THE MAIN COMPETITORS
Abstract
criteria. Among new learning criteria the criterion in the form of squared distance between main competitors with the penalty for wrong
decision has minor advantage. New criteria can be used not only for tuning fuzzy classifiers but for tuning some other models, such as neural networks.
Keywords
Full Text:
PDF (Українська)References
Kuncheva L. I. Fuzzy classifier design / L. I. Kuncheva //Studies in Fuzziness and Soft Computing. – Berlin – Heidelberg: Springer- Verlag, 2000. – Vol. 49. – 314 p. 2. Shtovba S. Analyzing the criteria for fuzzy classifier learning / S. Shtovba, O. Pankevich, A. Nagorna // Automatic Control and Computer Sciences. – 2015. – Vol. 49, № 3. – P. 123–132. 3. Madala H. R. Inductive learning algorithms for complex systems modeling / H. R. Madala, A. G. Ivakhnenko. – Boca Raton : CRC Press, 1994. – 368 p. 4. Bellman R. Abstraction and pattern classification / R. Bellman, R. Kalaba, L. Zadeh // Journal of Mathematical Analysis and Applications. – 1966. – Vol. 13, № 1. – P. 1–7. 5. Construction of fuzzy classification systems with rectangular fuzzy rules using genetic algorithms / [Ishibuchi H., Nozaki K., Yamomoto N., Tanaka H.] // Fuzzy sets and systems. – 1994. – Vol. 65, № 2. – P. 237–253. 6. Ishibuchi H. Classification and modeling with linguistic information granules: advanced approaches advanced approaches to linguistic data mining / H. Ishibuchi, T. Nakashima, M. Nii. – Berlin-Heidelberg : Springer-Verlag, 2005. – 307 p. 7. Штовба С. Д. Порівняння критеріїв навчання нечіткого класифікатора / С. Д. Штовба // Вісник Вінницького політехнічного інституту. – 2007. – № 6. – С. 84–91. 8. Abe S. Tuning of a fuzzy classifier derived from data / S. Abe, M. S. Lan, R. Thawonmas // International Journal of Approximate Reasoning. – 1996. – Vol. 14. – P. 1–24. 9. Nauck D. A neuro-fuzzy method to learn fuzzy classification rules from data / D. Nauck, R. Kruse // Fuzzy Sets and Systems. – 1997. – Vol. 89, № 3. – P. 277–288. 10. Rotshtein A. P. Design and Tuning of Fuzzy If – Then Rules for Automatic Classification / A. P. Rotshtein, D. I. Katelnikov // Proc. of NAFIPS’98 – International Conf. «Annual Meeting of North American Fuzzy Information Processing Society», Tampa, USA, 1998. – P. 50–55.
GOST Style Citations
Copyright (c) 2016 S. D. Shtovba, A. V. Galushchak

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Address of the journal editorial office:
Editorial office of the journal «Radio Electronics, Computer Science, Control»,
National University "Zaporizhzhia Polytechnic",
Zhukovskogo street, 64, Zaporizhzhia, 69063, Ukraine.
Telephone: +38-061-769-82-96 – the Editing and Publishing Department.
E-mail: rvv@zntu.edu.ua
The reference to the journal is obligatory in the cases of complete or partial use of its materials.