A k-nearest neighbor classification rule based on Dempster-Shafer theory

Studies in Fuzziness and Soft Computing

Volumn 219, Issue , 2008, Pages 737-760

  Denœux, Thierry ^a  

^a NONE

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EID: 38649124337     PISSN: 14349922     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-44792-4_29     Document Type: Article

References (21)

1. T. Baily and A. K. Jain, "A note on distance-weighted k-nearest neighbor rules," IEEE Trans. Syst. Man Cyber., vol. 8, no. 4, pp. 311-313, 1978.
2. W. F. Caselton and W. Luo, "Decision making with imprecise probabilities: Dempster-Shafer theory and application," Water Resources Research, vol. 28, no. 12, pp. 3071-3081, 1992.
3. C. K. Chow, "On optimum recognition error and reject tradeoff," IEEE Trans. Inform. Theory, vol. IT-16, pp. 41-46, 1970.
4. T. M. Cover and P. E. Hart, "Nearest neighbor pattern classiffication," IEEE Trans. Inform. Theory, vol. IT-13, no. 1, pp. 21-27, 1967.
5. B. V. Dasarathy, "Nosing around the neighborhood: A new system structure and classiffication rule for recognition in partially exposed environments," IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-2, no. 1, pp. 67-71, 1980.
6. B. V. Dasarathy, "Nearest neighbor norms: NN pattern classification techniques," IEEE Computer Society Press, Los Alamitos, CA, 1991.
7. A. P. Dempster and A. Kong, "Comment," Stat. Sci., vol. 2, no. 1, pp. 32-36, 1987.
8. D. H. Deterding, "Speaker normalization for automatic speech recognition," Ph.D. thesis, University of Cambridge, 1989.
9. B Dubuisson and M. Masson, "A statistical decision rule with incomplete knowledge about classes," Pattern Recognition, vol. 26, no. 1, pp. 155-165, 1993.
10. S. A. Dudani, "The distance-weighted k-nearest-neighbor rule," IEEE Trans. Syst. Man Cyber., vol. 6, pp. 325-327, 1976.
11. E. Fix and J. L. Hodges, "Discriminatory analysis, nonparametric discrimination: Consistency properties," Technical Report 4, USAF School of Aviation Medicine, Randolph Field, TX, 1951.
12. M. E. Hellman, "The nearest neighbor classiffication rule with a reject option," IEEE Trans. Syst. Man Cyber., vol. 3, pp. 179-185, 1970.
13. A. Jozwik, "A learning scheme for a fuzzy k-NN rule," Pattern Recognition Letters, vol. 1, pp. 287-289, 1983.
14. J.M. Keller, M. R. Gray, and J. A. Givens, "A fuzzy k-NN neighbor algorithm, IEEE Trans. Syst. Man Cyber., vol. 15, no. 4, pp. 580-585, 1985.
15. J. E. Macleod, A. Luk, and D. M. Titterington, "A re-examination of the distance-weighted k-nearest neighbor classiffication rule," IEEE Trans. Syst. Man Cyber., vol. 17, no. 4, pp. 689-696, 1987.
16. R. L. Morin and D. E. Raeside, "A reappraisal of distance-weighted k nearest-neighbor classiffication for pattern recognition with missing data," IEEE Trans. Syst. Man Cyber., vol. 11, no. 3, pp. 241-243, 1981.
17. P. M. Murphy and D.W. Aha, "UCI Repository of machine learning databases [Machine-readable data repository]," University of California, Department of Information and Computer Science., Irvine, CA, 1994.
18. A. J. Robinson, "Dynamic error propagation networks," Ph.D. thesis, Cambridge University Engineering Department, 1989.
19. G. Shafer, A Mathematical Theory of Evidence. Princeton, NJ: Princeton University Press, 1976.
20. V. G. Sigillito, S. P. Wing. L. V. Hutton, and K. B. Baker, "Classiffication of radar returns from the ionosphere using neural networks," in Johns Hopkins APL Technical Digest, vol. 10, pp. 262-266, 1989.
21. B. Tessem, "Approximations for efficient computation in the theory of evidence," Artificial Intelligence, vol. 61, pp. 315-329, 1993.