Heuristic possibilistic clustering for detecting optimal number of elements in fuzzy clusters

[1] Anderson E., The irises of the Gaspe Peninsula, Bulletin of the American Iris Society, 59, 1, 1935, 2-5.Search in Google Scholar

[2] Bezdek J.C., Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York, 1981.10.1007/978-1-4757-0450-1Search in Google Scholar

[3] Chiang J.-H., Yue S., Yin Z.-X., A new fuzzy cover approach to clustering, IEEE Transactions on Fuzzy Systems, 12, 2, 2004, 199-208.10.1109/TFUZZ.2004.825076Search in Google Scholar

[4] Corsini P., Lazzerini B., Marcelloni F., A new fuzzy relational clustering algorithm based on the fuzzy C-means algorithm, Soft Computing, 9, 6, 2005, 439-447.10.1007/s00500-004-0359-6Search in Google Scholar

[5] De Cáceres M., Oliva F., Font X., On relational possibilistic clustering, Pattern Recognition, 39, 11, 2006, 2010-2024.10.1016/j.patcog.2006.04.008Search in Google Scholar

[6] Everitt B.S., Landau S., Leese M., Stahl D., Cluster Analysis, 5th Edition, Wiley, Chichester, 2011.10.1002/9780470977811Search in Google Scholar

[7] Hamasuna Y., Endo Y., Miyamoto S., Fuzzy C-means clustering for data with clusterwise tolerance based on L₂- and L₁-regularization, Journal of Advanced Computational Intelligence and Intelligent Informatics, 15, 1, 2011, 68-75.10.20965/jaciii.2011.p0068Search in Google Scholar

[8] Höppner F., Klawonn F., Kruse R., Runkler T., Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition, John Wiley & Sons, Chichester, 1999.Search in Google Scholar

[9] Kaufmann A., Introduction to the Theory of Fuzzy Subsets, Academic Press, New York, 1975.Search in Google Scholar

[10] Komazaki Y., Miyamoto S., Variables for controlling cluster sizes on fuzzy C-means, in: V. Torra, Y. Narukawa, G. Navarro-Arribas, D. Megías (eds.), Modeling Decisions for Artificial Intelligence: Proceedings of the 10th International Conference MDAI’2013, Barcelona, Spain, November 20-22, 2013, Springer, Berlin, 2013, 192-203.Search in Google Scholar

[11] Krishnapuram R., Keller J.M., A possibilistic approach to clustering, IEEE Transactions on Fuzzy Systems, 1, 2, 1993, 98-110.10.1109/91.227387Search in Google Scholar

[12] Łęski J.M., Robust possibilistic clustering, Archives of Control Sciences, 10, 3/4, 2000, 141-155.Search in Google Scholar

[13] Mandel I.D., Clustering Analysis, Finansy i Statistica, Moscow, 1988. (in Russian)Search in Google Scholar

[14] Ménard M., Courboulay V., Dardignac P.-A., Possibilistic and probabilistic fuzzy clustering: unification within the framework of the non-extensive thermostatistics, Pattern Recognition, 36, 6, 2003, 1325-1342.10.1016/S0031-3203(02)00049-3Search in Google Scholar

[15] Miyamoto S., Ichihashi H., Honda K., Algorithms for Fuzzy Clustering. Methods in C-Means Clustering with Applications, Springer, Berlin, 2008.Search in Google Scholar

[16] Miyamoto S., Different objective functions in fuzzy C-means algorithms and kernel-based clustering, International Journal of Fuzzy Systems, 13, 2, 2011, 89-97.Search in Google Scholar

[17] Pedrycz W., Fuzzy sets in pattern recognition: methodology and methods, Pattern Recognition, 23, 1/2, 1990, 121-146.10.1016/0031-3203(90)90054-OSearch in Google Scholar

[18] Sato-Ilic M., Jain L.C., Innovations in Fuzzy Clustering. Theory and Applications, Springer, Berlin, 2006.Search in Google Scholar

[19] Sneath P.H.A., Sokal R., Numerical Taxonomy, Freeman, San Francisco, 1973.Search in Google Scholar

[20] Tamura S., Higuchi S., Tanaka, K., Pattern classification based on fuzzy relations, IEEE Transactions on Systems, Man, and Cybernetics, 1, 1, 1971, 61-66.10.1109/TSMC.1971.5408605Search in Google Scholar

[21] Vapnik V.N., Statistical Learning Theory, Wiley, New York, 1998.Search in Google Scholar

[22] Viattchenin D.A., A Heuristic Approach to Possibilistic Clustering: Algorithms and Applications, Springer, Berlin, 2013.10.1007/978-3-642-35536-3Search in Google Scholar

[23] Viattchenin D.A., Damaratski A., Direct heuristic algorithms of possibilistic clustering based on transitive approximation of fuzzy tolerance, Informatica Economicá Journal, 17, 3, 2013, 5-15.10.12948/issn14531305/17.3.2013.01Search in Google Scholar

[24] Viattchenin D.A., Yaroma A., Damaratski A., A novel direct relational heuristic algorithm of possibilistic clustering, International Journal of Computer Applications, 107, 18, 2014, 15-21.10.5120/18850-0381Search in Google Scholar

[25] Walesiak M., Ugólniona Miara Odległości w Statystycznej Analizie Wielowymiarowej, Wydawnictwo Akademii Ekonomicznej im. Oskara Langego, Wrocław, 2002. (in Polish)Search in Google Scholar

[26] Xie Z., Wang S.T., Chung F.L., An enhanced possibilistic c-means clustering algorithm EPCM, Soft Computing, 12, 6, 2008, 593-611.10.1007/s00500-007-0231-6Search in Google Scholar

[27] Yang M.-S., Wu K.-L., Unsupervised possibilistic clustering, Pattern Recognition, 39, 1, 2006, 5-21.10.1016/j.patcog.2005.07.005Search in Google Scholar