Linear fuzzy clustering of relational data based on extended fuzzy c-medoids

IEEE International Conference on Fuzzy Systems

Volumn , Issue , 2008, Pages 366-371

  Haga, Naoki ^a   Honda, Katsuhiro ^a   Ichihashi, Hidetomo ^a   Notsu, Akira ^a  

^a Osaka Prefecture University   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; COMBINATORIAL MATHEMATICS; COMBINATORIAL OPTIMIZATION; DATA HANDLING; DATA STRUCTURES; FLOW OF SOLIDS; FUZZY LOGIC; FUZZY RULES; FUZZY SETS; FUZZY SYSTEMS;

CLUSTERING CRITERION; COMBINATORIAL OPTIMIZATION PROBLEMS; DATA SAMPLES; FCM ALGORITHMS; FUZZY C-MEANS; ITERATIVE PROCEDURES; LINEAR FUZZY CLUSTERING; LOCAL LINEAR; MEDOIDS; MEMBERSHIP VALUES; MODIFIED ALGORITHMS; MULTI-DIMENSIONAL; MUTUAL DISTANCES; NUMERICAL EXPERIMENTS; RELATIONAL DATUMS; REPRESENTATIVE OBJECTS;

FUZZY CLUSTERING;

EID: 55249103406     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2008.4630392     Document Type: Conference Paper

References (12)

1. J. C. Bezdek. C. Coray, R. Gunderson and J. Watson, "Detection and characterization of cluster substructure 1. linear structure fuzzy c-lines," SIAM J. Appl. Math., vol. 40, no. 2, pp. 339-357, 1981.
2. J. C. Bezdek. C. Coray, R. Gunderson, and J. Watson. "Detection and characterization of cluster substructure 2. fuzzy c-varieties and convex combinations thereof," SIAM J. Appl. Math., vol. 40, no. 2. pp. 358-372, 1981.
3. J. C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, 1981.
4. K. Honda and H. Ichihashi, "Linear fuzzy clustering techniques with missing values and their application to local principal component analysis," IEEE Trans. Fuzzy Systems, vol. 12, no. 2, pp. 183-193, 2004.
5. K. Honda and H. Ichihashi, "Regularized linear fuzzy clustering and probabilistic PCA mixture models," IEEE Trans. Fuzzy Systems, vol. 13, no. 4, pp. 508-516. 2005.
6. Y. Yabuuchi and J. Watada, Fuzzy principal component analysis and its application. Biomedical Fuzzy and Human Sciences, vol. 3, pp. 83-92. 1997.
7. L. Kaufman and P. J. Rousseeuw, Finding Groups In Data: An Introduction To Cluster Analysis. Wiley-Interscience, 1990.
8. J. B. MucQueen, Some methods of classification and analysis of multivariate observations, Proc. of 5th Berkeley Symposium on Math. Stat, and Prob., pp. 281-297, 1967.
9. R. Krishnapuram, A. Joshi, O. Nusraoui and L. Yi, Low-complexity fuzzy relational clustering algorithms for web mining. IEEE Trans. Fuzzy Systems, vol. 9, no. 4, pp. 595-607, 2001.
10. W. S. Torgerson. Theory & Methods of Scaling. Wiley, 1958.
11. G. Ekman, "Dimensions of color vision," Journal of Psychology, vol. 38, pp. 467-474, 1954.
12. C. Hayushi, "On the prediction of phenomena from qualitutive data and the quantification of qualitative data from the mathematical statistical point of view." Annals of the Institute of Statistical Mathematics, vol. 3, pp. 69-98. 1952.