147
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

A probabilistic clustering method for data elements with normal distributed attributes

&
Pages 2563-2575 | Received 01 Sep 2014, Accepted 07 May 2015, Published online: 18 Dec 2016

References

  • Atashpaz-Gargari, E., Lucas, C. (2007). Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition. In: IEEE Congress on Evolutionary Computation, 2007. CEC 2007. IEEE, Red Hook, USA: Curran Associates, Inc., pp. 4661–4667.
  • Bezdek, J. C. (1981). Pattern Recognition with Fuzzy Objective Function Algorithms. Norwell, MA, USA: Kluwer Academic Publishers.
  • Chen, M.-Y., Linkens, D. A. (2004). Rule-base self-generation and simplification for data-driven fuzzy models. Fuzzy Sets and Systems 142(2):243–265.
  • Chuan Tan, S., Ming Ting, K. and Wei Teng, S. (2011). A general stochastic clustering method for automatic cluster discovery. Pattern Recognition 44(10–11):2786–2799.
  • Coppi, R., D'urso, P., Giordani, P. (2012). Fuzzy and possibilistic clustering for fuzzy data. Computational Statistics & Data Analysis 56(4):915–927.
  • Gath, I., Geva, A. B. (1989). Unsupervised optimal fuzzy clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 11(7):773–780.
  • Gdalyahu, Y., Weinshall, D., Werman, M. (2001). Self-organization in vision: Stochastic clustering for image segmentation, perceptual grouping, and image database organization. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(10):1053–1074.
  • Gustafson, D. E., Kessel, W. C. (1978). Fuzzy clustering with a fuzzy covariance matrix. In: IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes. IEEE, New York, USA: Publishing Services, IEEE, pp. 761--766.
  • Hatamlou, A. (2013). Black hole: A new heuristic optimization approach for data clustering. Information Sciences 222:175–184.
  • Herbin, M., Bonnet, N., Vautrot, P. (1996). A clustering method based on the estimation of the probability density function and on the skeleton by influence zones. Application to image processing. Pattern Recognition Letters 17(11):1141–1150.
  • Negreiros, M., Palhano, A. (2006). The capacitated centered clustering problem. Computers & Operations Research 33(6):1639–1663.
  • Ruspini, E. H. (1969). A new approach to clustering. Information and Control 15(1):22–32.
  • Ruspini, E. H. (1970). Numerical methods for fuzzy clustering. Information Sciences 2(3):319–350.
  • Ruspini, E. H. (1973). New experimental results in fuzzy clustering. Information Sciences 6(0):273–284.
  • Viattchenin, D. A. (2008). A heuristic approach to possibilistic clustering for fuzzy data. Journal of Information and Organizational Sciences 32(2):149--163.
  • Wang, W., Zhang, Y. (2007). On fuzzy cluster validity indices. Fuzzy Sets and Systems 158(19):2095–2117.
  • Wang, X., Yang, C., Zhou, J. (2009). Clustering aggregation by probability accumulation. Pattern Recognition 42(5):668–675.
  • Zadeh, L. A. (2002). Probability Theory and Fuzzy Logic. Available at: www.Ieeesmc.org/dec2002/Probability%20Theory%20and%20Fuzzy%20Logic.Pdf.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.