Abstract
It has been observed that in the previous Genetic Algorithms (GA) based Fuzzy Clustering (FC) works only some of the parameters of an FC system are developed. Here, a new approach is proposed to develop directly the membership functions for the clusters using GA. This new technique is implemented and tested on common test data. A comparative study of the results against the quotations in literature reveals that the standard c-means FC technique is outperformed by the proposed technique in the count of misclassifications aspect.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
R.E. Bellman, R.A. Kalaba, and L.A. Zadeh.: Abstraction and pattern classification. Journal of Math. Anal. Appl., 13:1–7, 1966.
I. Gitman and M. Levine.: An algorithm for detecting unimodal fuzzy sets and its application as a clustering technique. IEEE Trans. Computers, 19:917–923, 1970.
E.H. Ruspini.: A new approach to clustering. Information and Control, 15:22–32, 1969.
J. Dunn.: A fuzzy relative of the isodata process and its use in detecting compact well-seperated clusters. Journal of Cybernetics, 3:32–57, 1974.
J. Bezdek and R. Hathaway.: Optimization of fuzzy clustering criteria using genetic algorithms. In Proc. of First IEEE Conf. on Evalutionary Computation, number 589–594, Orlando, 1994.
L.O. Hall, J.C. Bezdek, S. Boggavarpu, and A. Bensaid.: Genetic fuzzy clustering. In Int.Proc. North American Fuzzy Information Processing Society Biannual Conferance (NAFIPS'94), pages 411–415, San Antonio, 1994.
J. Liu and W. Xie.: A genetic-based approach to fuzzy clustering. In Proc. of Fourth IEEE Int. Conf. on Fuzzy Systems, pages 2233–2237, Yokohama, 1995.
T.V. Le.: Evolutionary fuzzy clustering. In Second IEEE Conf. on Evolutionary Computation, volume 2, Perth, 1995.
B. Yuan, G.J. Klir, and J.F. Swan-Stone.: Evolutionary fuzzy C-Means clustering algorithm. In Proc. Fourth IEEE Int. Conf. on Fuzzy Systems, pages 2221–2226, 1995.
R. Srikanth, R. George, N. Warsi, D. Prabhu, F.E. Petry, and B.P. Buckles.: A variable-length genetic algorithm for clustering and classification. Pattern Recognition Letters, 16:789–800, 1995.
Y.S. Kim and S. Mitra.: Integrated adaptive fuzzy clustering algorithm. In Proc. of Int. Conf. on Fuzzy Systems, pages 1264–1268, San Francisco, March 1993.
M.S. Kamel and S.Z. Selim.: A relaxation approach to the fuzzy clustering problem. Fuzzy Sets and Systems, 61:177–188, 1994.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag
About this paper
Cite this paper
Turhan, M. (1997). Genetic Fuzzy Clustering by means of discovering membership functions. In: Liu, X., Cohen, P., Berthold, M. (eds) Advances in Intelligent Data Analysis Reasoning about Data. IDA 1997. Lecture Notes in Computer Science, vol 1280. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0052856
Download citation
DOI: https://doi.org/10.1007/BFb0052856
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63346-4
Online ISBN: 978-3-540-69520-2
eBook Packages: Springer Book Archive