Accession number:20100212619079
Title: Fuzzy C-means algorithm based on common mahalanobis distances
Authors: Liu, Hsiang-Chuan (1); Yih, Jeng-Ming (2); Lin, Wen-Chih (3);
Wu, Der-Bang (2)
Author affiliation:(1) Department of Bioinformatics, Asia University, 500, Lioufeng Rd., Wufeng, Taichung, 41354, Taiwan; (2) Graduate Institute of Educational Measurement and Statistics, Department of Mathematics Education, National Taichung University, No. 140, Ming- sheng Road, Taichung, 40306, Taiwan; (3) Department of Computer Science and Information Engineering, Asia University, 500, Lioufeng Rd., Wufeng, Taichung, 41354, Taiwan
Corresponding author:Wu, D.-B.
Source title: Journal of Multiple-Valued Logic and Soft Computing Abbreviated source title:J. Mult.-Valued Logic Soft Comput.
Volume:15 Issue:5-6
Issue date:2009
Publication year:2009 Pages:581-595
Language:English ISSN:15423980
Document type:Journal article (JA)
Publisher:Old City Publishing, 628 North 2nd Street, Philadelphia, PA 19123, United States
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. © 2009 Old City Publishing, Inc.
Number of references:18
Main heading:Clustering algorithms
Controlled terms: Color - Copying - Covariance matrix - Fuzzy clustering - Fuzzy rules - Fuzzy systems
Uncontrolled terms: FCM-CM algorithm. - FCM-M algorithm - Fuzzy C- Means algorithm - Fuzzy C-means algorithms - M-algorithms
Classification code:922 Statistical Methods - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory - 921 Mathematics - 903.2 Information Dissemination - 903.1 Information Sources and Analysis - 961 Systems Science - 745.2 Reproduction, Copying - 731.1 Control Systems - 723.4 Artificial Intelligence - 723 Computer Software, Data Handling and Applications - 721 Computer Circuits and Logic Elements - 741.1 Light/Optics
Database:Compendex
