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Fuzzy C-Means Algorithm Based on Common Mahalanobis Distances

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Author(s): Liu, HC (Liu, Hsiang-Chuan); Yih, JM (Yih, Jeng-Ming); Lin, WC (Lin, Wen-Chih);

Wu, DB (Wu, Der-Bang)

Title: Fuzzy C-Means Algorithm Based on Common Mahalanobis Distances

Source: JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING, 15 (5-6): 581- 595 2009

Language: English Document Type: Article

Author Keywords: Fuzzy C-Means algorithm; GK-algorithm; GG-algorithm; FCM-M algorithm; FCM-CM algorithm

Abstract: Some of the well-known fuzzy clustering algorithms are based on Euclidean distance function, which can only be used to detect spherical structural clusters. Gustafson- Kessel (GK) clustering algorithm and Gath-Geva (GG) clustering algorithm were developed to detect non-spherical structural clusters. However, GK algorithm needs added constraint of fuzzy covariance matrix, GK algorithm can only be used for the data with multivariate

Gaussian distribution. A Fuzzy C-Means algorithm based on Mahalanobis distance (FCM-M) was proposed by our previous work to improve those limitations of GG and GK algorithms, but it is not stable enough when some of its covariance matrices are not equal. In this paper, A improved Fuzzy C-Means algorithm based on a Common Mahalanobis distance (FCM-CM) is proposed The experimental results of three real data sets show that the performance of our proposed FCM-CM algorithm is better than those of the FCM, GG, GK and FCM-M algorithms.

Addresses: [Yih, Jeng-Ming; Wu, Der-Bang] Natl Taichung Univ, Grad Inst Educ

Measurement & Stat, Dept Math Educ, Taichung 40306, Taiwan; [Liu, Hsiang-Chuan] Asia Univ, Dept Bioinformat, Taichung 41354, Taiwan; [Lin, Wen-Chih] Asia Univ, Dept Comp Sci &

Informat Engn, Taichung 41354, Taiwan

Reprint Address: Wu, DB, Natl Taichung Univ, Grad Inst Educ Measurement & Stat, Dept Math Educ, 140 Ming Sheng Rd, Taichung 40306, Taiwan.

E-mail Address: [email protected]; [email protected]; [email protected];

[email protected] Funding Acknowledgement:

Funding Agency Grant Number

National Science Council of Taiwan NSC 98-2410-H-468-014

This paper is partially supported by the grant National Science Council of Taiwan (NSC 98- 2410-H-468-014).

Cited References: BALASKO B, FUZZY CLUSTERING DAT.

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Cited Reference Count: 17 Times Cited: 0

Publisher: OLD CITY PUBLISHING INC

Publisher Address: 628 NORTH 2ND ST, PHILADELPHIA, PA 19123 USA ISSN: 1542-3980

29-char Source Abbrev.: J MULT-VALUED LOG SOFT COMPUT ISO Source Abbrev.: J. Mult.-Valued Log. Soft Comput.

Source Item Page Count: 15

Subject Category: Computer Science, Artificial Intelligence; Computer Science, Theory &

Methods

ISI Document Delivery No.: 516GP

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