Computationally effective algorithm to the ε-Insensitive fuzzy clustering

Systems Science

Volumn 28, Issue 3, 2003, Pages 31-50

  Łeski, Jacek ^a  

^a SILESIAN UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; DATA MINING; IMAGE PROCESSING; PATTERN RECOGNITION; PROBLEM SOLVING;

SYSTEM MODELING;

FUZZY SETS;

EID: 0038723229     PISSN: 01371223     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (19)

1. BEZDEK J. C., Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York 1982.
2. DAVÉ R. N., Characterization and Detection of Noise in Clustering, Pattern Recognition Lett., Vol. 12, No. 11, 1991, 657-664.
3. DAVÉ R. N., KRISHNAPURAM R., Robust Clustering Methods: A Unified View, IEEE Trans. Fuzzy Systems, Vol. 5, No. 2, 1997, 270-293.
4. DUDA R. O., HART P. E., Pattern Classification and Scene Analysis, John Wiley & Sons, New York 1973.
5. DUNN J. C., A Fuzzy Relative of the ISODATA Process and its Use in Detecting Compact Well-Separated Cluster, Journal Cybernetics, Vol. 3, No. 3, 1973, 32-57.
6. FUKUNAGA K., Introduction to Statistical Pattern Recognition, Academic Press, San Diego 1990.
7. p Norm Distances, IEEE Trans. Fuzzy Systems, Vol. 8, No. 5, 2000, 576-582.
8. HUBER P. J., Robust statistics, Wiley, New York 1981.
9. 1-norm based fuzzy clustering, Fuzzy Sets & Systems, Vol. 39, No. 1, 1991, 43-50.
10. KERSTEN P. R., Fuzzy Order Statistics and Their Application to Fuzzy Clustering, IEEE Trans. Fuzzy Systems, Vol. 7, No. 6, 1999, 708-712.
11. KRISHNAPURAM R., KELLER J. M., A Possibilistic Approach to Clustering, IEEE Trans. Fuzzy Systems, Vol. 1, No. 1, 1993, 98-110.
12. ŁESKI J., Robust possibilistic clustering, Archives of Control Sciences, Vol. 10, No. 3-4, 2000, 141-155.
13. ŁeSKI J., An ε-insensitive approach to fuzzy clustering, International Journal Applied Mathematics and Computer Sciences, Vol. 11, No. 4, 2001, 993-1007.
14. NAVIA-VÁZQUEZ A., PÉREZ-CRUZ F., ARTÉS-RODRÍGUEZ A. R., FIGUEIRAS-VIDAL A. R., Weighted Least Squares Training of Support Vector Classifiers Leading to Compact and Adaptive Schemes, IEEE Trans. Neural Networks, Vol. 12, No. 5, 2001, 1047-1059.
15. PAL N. R., BEZDEK J. C., On Cluster Validity for the Fuzzy c-Means Model, IEEE Trans. Fuzzy Systems, Vol, 3, No. 3, 1995, 370-379.
16. RUSPINI E. H., A New Approach to Clustering, Inform. Control, Vol. 15, No. 1, 1969, 22-32.
17. TOU J. T., GONZALEZ R. C., Pattern Recognition Principles, Addison-Wesley, London 1974.
18. VAPNIK V., Statistical Learning Theory, Wiley, New York 1998.
19. ZADEH L. A., Fuzzy Sets, Information and Control, Vol. 8, 1965, 338-353.