Fuzzy belief pattern classification of incomplete data

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

Volumn , Issue , 2007, Pages 535-540

  Chou, Te Shun ^a   Yen, Kang K ^a   An, Liwei ^b   Pissinou, Niki ^c   Makki, Kia ^c  

^a Florida International University   (United States)

^b University of Rochester   (United States)

^c FLORIDA INTERNATIONAL UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA REDUCTION; DATA STRUCTURES; DECISION TABLES; FUZZY SETS; LEARNING ALGORITHMS;

DECISION RULE SET; DEMPSTER-SHAFER THEORY;

PATTERN RECOGNITION;

EID: 40949139732     PISSN: 1062922X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSMC.2007.4413848     Document Type: Conference Paper

References (14)

1. J. C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York, 1981.
2. C. L. Blake and C. J. Merz, UCI Repository of Machine Learning Databases, 1998.
3. A. P. Dempster, "A Generalization of Bayesian Inference," Journal of the Royal Statistical Society, Series B, vol. 30, pp. 205-247, 1968.
4. A.P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum Likelihood From Incomplete Data via the EM Algorithm," Journal Royal Statistical Society Series, B 39, pp. 1-38, 1977.
5. T. Denoeux, "A k-Nearest Neighbor Classification Rule Based on Dempster-Shafer Theory," IEEE Transactions on Systems, Man and Cybernetics, vol. 25, no. 5, pp. 804-813, May 1995.
6. T. Denoeux, "A Neural Network Classifier Based on Dempster-Shafer Theory," IEEE Transactions on Systems, Man and Cybernetics, vol. 30, no. 2, pp. 131-150, March 2000.
7. J. C. Dunn, "A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters", Journal of Cybernetics vol. 3, p.p. 32-57, 1973.
8. P. D. Green, J. Barker, M. P. Cooke and L. Josifovski, "Handling Missing and Unreliable Information in Speech Recognition," in Proceedings of International Workshop on AI and Statistics, 2001.
9. R. J. Hathaway and J. C. Bezdek, "Fuzzy c-Means Clustering of Incomplete Data," IEEE Transactions on Systems, Man, and Cybernetics, vol. 31, no. 5, pp. 735-744, October 2001.
10. D. Rubin, Multiple Imputation for Nonresponse in Surveys, New York, Wiley, 1987.
11. G. Shafer, A Mathematical Theory of Evidence, Princeton, University Press, Princeton, NJ, 1976.
12. V. Tresp, R. Neunier and S. Ahmad, "Efficient Methods for Dealing with Missing Data in Supervised Learning," Advances in Neural Information Processing System, 1995.
13. nd International Conference on Machine Learning, Bonn, Germany, August 2005.
14. J. Zhang, S. P. Subasingha, K. Premaratne, M. L. Shyu, M. Kubat and K. K. R. G. K Hewawasam, "A Rule Mining Based Belief Theoretic Algorithm for Security Monitoring and Threat Classification," in Foundations of Data Mining workshop of Fourth International Conference on Data Mining, Bright, UK, 2004.