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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 40-41Research on Fuzzy Clustering Validity

Research on Fuzzy Clustering Validity

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Abstract:

The evaluation of clustering validity is important for clustering analysis, and is one of the hottest spots of cluster analysis. The quality of the evaluation of clustering is that optimal number of clusters is reasonable. For fuzzy clustering, the paper surveys the widely known fuzzy clustering validity evaluation based on the methods of fuzzy partition, geometry structure and statistics.

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Advances in Science and Engineering

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Periodical:

Applied Mechanics and Materials (Volumes 40-41)

Pages:

174-182

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.40-41.174

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Cite this paper

Online since:

November 2010

Authors:

Wei Jin Chen, Huai Lin Dong, Qing Feng Wu, Ling Lin

Keywords:

Fuzzy Clustering, Optimal Number of Clusters, Validity Evaluation Function

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] Halkid, Vazirgiannis and Batistakis: Quality Scheme Assessment in the Clustering Process. Proc of the 4th Eur Conf Principles and Practice of Knowledge Discovery in Databases, (2000).

[2] Zadeh: Fuzzy Logic. IEEE Trans, (1988).

[3] Bezdek: Cluster Validity with Fuzzy sets. Mathematical Biology, (1974).

[4] Xinbo Gao, in: Fuzzy Cluster Analysis and its Applications, edited by Xinbo Gao, chapter, 9, Xidian university (2004).

[5] Jiulun Fan, Jihong Pei and Weixin Xie: Cluster Validity Based on Possibilistic Distribution. ACTA ELECTRONICA SINICA. Forum Vol. 26 (1998), pp.127-130.

[6] Shannon: A Mathematical Theory of Communication. Bell Syst Tech, (1948).

[7] Caizhi Sun, Jingdong Wang and Jun Pan: Research on the Method of Determining the Optimal Class Number of Fuzzy Cluster. Fuzzy Systems and Mathematics. Forum Vol. 15 (2001), pp.89-91.

[8] Dunn: Well-separated clusters and the optimal fuzzy partitions. Journal of Cybernet. Forum Vol. 14 (1974), pp.95-104.

[9] A. M. Bensaid, L. O. Hall, J. C. Bezdek, L. P. Clarke, M. L. Sibiger and J. A. Arrington, et al: "Validity Guided(Re) Clustering with Applications to Image Segmentation. IEEE Trans. Forum Vol. 4 (1996), pp.112-122.

DOI: 10.1109/91.493905

[10] Kwon: Cluster Validity Index for Fuzzy Clustering. Electronics Letters. Forum Vol. 34 (1998), pp.2176-2177.

DOI: 10.1049/el:19981523

[11] Zhengyi Bao: Research on Fuzzy Clustering Algorithm and Validity Index. Master dissertation, Xiamen University. (2006).

[12] Pan Kong, Huiwen Deng, Yanyan Huang, Huan Jiang: Novel Validity Index for Fuzzy Clustering. Computer Engineering. Forum Vol. 35 (2009), pp.143-144.

[13] Jing An, Qingshan Jiang: A Novel Validity Index for Fuzzy Clustering. Journal of Computer Research and Development. Forum Vol. 42 (2005), pp.38-42.

[14] Yong Peng, Youqing Wu: New Cluster Validity Function for Determining Cluster Number. Computer Engineering and Applications. Forum Vol. 46 (2010), pp.124-126.

[15] Weihua Ou: Fuzzy Clustering Validity Function Based on the Increment of Overlap. Computing Technology and Automation. Forum Vol. 28 (2009), pp.115-116.

[16] Kim Young-Il, Kim Dao-Won, Lee Doheon and Lee Kwang H: A cluster validation index for GK cluster analysis based on relative degree of sharing. Information sciences. Forum Vol. 168 (2004), pp.225-242.

DOI: 10.1016/j.ins.2004.02.006

[17] Kim Dao-Won, Lee Kwang H and Lee Doheon: On cluster validity index for estimation of the optimal number of fuzzy clusters. Pattern Recognition Letters. Forum Vol. 37 (2004).

DOI: 10.1016/j.patcog.2004.04.007

[18] Shenglan Ben and Guangda Su: A New Validity Index Based on Intra-cluster Variation and Inter-cluster overlap. Journal of Optoelectronics Laser. Forum Vol. 21 (2010), pp.298-301.

[19] MY Chen and DA Linkens: Rule_based self-generation and simplification for sata_driven fuzzy models. Fuzzy Sets and System. Forum Vol. 142 (2004).

DOI: 10.1016/s0165-0114(03)00160-x

[20] Yingchun zhou and Jiawei Luo: Application Research of Fuzzu Cliustering Analysis Based on Graphical Representation of DNA Sequences. Journal of WUT(Information & Management Engineering). Forum Vol. 31 (2009), pp.26-27.

[21] Yi Dong and Yang Michael: Gene Expression Clustering By Pseudo F-statistics Method. Chinese Journal of Health Statistics. Forum Vol. 19 (2002).

[22] Zhonghua An and Qiong An: the Study on the Validity of Fuzzy Cluster, " Journal of Hubei University. Journal of Hubei University. Forum Vol. 28 (2006), pp.221-226.