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Scientific-technical journal

Abstract

In this work, we consider one of the tasks of data mining, the problem of classification. It uses algorithms of the logical model of fuzzy classification and algorithms of k nearest neighbors. In the process of building a fuzzy logic model, in some cases, some methods from the base of fuzzy rules were used by the method of mountain clustering. In addition, the article proposes a new method for constructing a base of fuzzy rules, using the method of fuzzy clustering. In addition, in the article, the problem of classifying the Iris flower was solved based on some classification algorithms and the results were compared.

First Page

68

Last Page

73

References

[1] Baskin II, Palyulin VA Zefirov NS Multilayer perceptrons in the study of dependence "structure-property" for organic compounds / Russian Chemical Journal (Journal of the Russian Chemical Society. Mendeleev). - 2006. - T. 50. - P. 86-96.

[2] Rotshteyn A.P. Intellektualnie texnologii identifikatsii: nechetkaya logika, geneticheskie algoritmi, neyronnie seti. -Vinnitsa: UNIVERSUM-Vinnitsa. 1999.-320 s.

[3] Rutkovskaya D., Pilinskiy M., Rutkovskiy L. Neyronnie seti, geneticheskie algoritmi i nechetkie sistemi: Per.s polsk. I.D. Rudinskogo. -M.: Goryachaya liniya-Telekom, 2004. -452 s.

[4] Minglikulov Z.B. Algoritmi prinyatiya diagnosticheskix resheniy s ispolzovaniem neyronechetkix texnologiy// Uzb.jurn. “Problemы informatiki i energetiki”. – Toshkent, 2011. - №1. – S. 71-76.

[5] SHtovba S.D. "Vvedenie v teoriyu nechetkix mnojestv i nechetkuyu logiku". http//www.matlab.exponenta.ru.

[6] Leonenkov A.V. Nechetkoe modelirovanie v srede MATLAB i fuzzyTECH. – SPb., 2003.

[7] Mingliqulov Z.B. Turli tegishlilik funktsiyalarida neyronoravshan to’rni o’qitish va sinflashtirish masalalarini yechish // Materiali Respublikanskoy nauchno-texnicheskoy konferentsii «Sovremennoe sostoyanie i perspektivi razvitiya informatsionnix texnologiy». Tashkent. – 2011. –s. 347-352.

[8] Abidin, T. and Perrizo, W. SMART-TV: A Fast and Scalable Nearest Neighbor Based Classifier for Data Mining. Proceedings of ACM SAC-06, Dijon, France, April 23-27, 2006. ACM Press, New York, NY, pp.536-540

[9] Wang, H. and Bell, D. Extended k-Nearest Neighbours Based on Evidence Theory. The Computer Journal, Vol. 47 (6) Nov. 2004, pp. 662-672.

[10] Yu, K. and Ji, L. Karyotyping of Comparative Genomic Hybridization Human Metaphases Using Kernel Nearest-Neighbor Algorithm, Cytometry 2002.

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