Open Access Open Access  Restricted Access Subscription or Fee Access

Fuzzy Clustering Algorithms - Different Methodologies and Parameters - A Survey

B.S. Charulatha, Dr. Paul Rodrigues, Dr.T. Chitralekha

Abstract


Fuzzy clustering algorithms are helpful when there exists a dataset with sub groupings of points having indistinct boundaries and overlap between the clusters. This paper gives an overview of different classical fuzzy clustering algorithm. The fuzzy clustering algorithms can be categorized as classical fuzzy clustering and shape based clustering. The paper describes about the general working behavior, the methodologies followed on these approaches and the parameters which affects the performance of classical fuzzy clustering algorithms.


Keywords


Fuzzy Clustering, Classical Fuzzy Clustering Shape Based Clustering.

Full Text:

PDF

References


Jiawei Han, Micheline Kamber, “Data Mining Concepts and Techniques” Elsevier Publication

Wagstaff K., Cardie C., Rogers S. and Schrödl S. (2001). Constrained k-means clustering with Background Knowledge. Proceedings of the 18th International Conference on Machine Learning, 577-584.

Suh S.C., Saffer S. and Adla N.K. (2008). Extraction of Meaningful Rules in a Medical Database. Proceedings of the 7th International Conference on Machine Learning and Applications, 450-456

Alka Singla , Rajesh Mehra Design & Analysis Of Fuzzy Clustering Algorithm For Data Partitioning Applications International Journal of VLSI and Signal Processing Applications, Vol. 1, Issue 2 , May 2011,(52-56) ,ISSN 2231-3133

David J.Miller, Carl A. Nelson, Molly Boeka Cannon, and Kenneth P. Cannon Comparison of Fuzzy ClusteringMethods and Their Applications to Geophysics Data Applied Computational Intelligence and Soft Computing Volume 2009, Article ID 876361, 16 pages

Horatiu Mocian Survey of Distributed Clustering Techniques

Muller,K.-R.; Mika, S.; Ratsch, G.; Tsuda, K.; Scholkopf, B,"An introduction to kernel-based learning algorithms"; Neural Networks, IEEE Transactions on Volume: 12 , Issue: 2 2001 , Page(s): 181 – 201

Dao-Qiang Zhang, Song-Can Chen Clustering incomplete data using kernel-based fuzzy c-means algorithm

R. Babuˇska P.J. van der Veen U. Kaymak Improved Covariance Estimation for Gustafson-Kessel Clustering 0-7803-7280-8/02 ©2002 IEEE

Hossein Soleimani-B. • Caro Lucas • Babak N. Araabi Recursive Gath–Geva clustering as a basis for evolving neuro-fuzzy modeling Evolving Systems Springer-Verlag 2010


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.