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Improved Evidence Theoretic kNN Classifier based on Theory of Evidence
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 15 - Number 5 |
| Year of Publication: 2011 |
| Authors: P.Umar Sathic Ali, Dr.C.Jothi Ventakeswaran |
10.5120/1943-2597
|
P.Umar Sathic Ali, Dr.C.Jothi Ventakeswaran . Improved Evidence Theoretic kNN Classifier based on Theory of Evidence. International Journal of Computer Applications. 15, 5 ( February 2011), 37-41. DOI=10.5120/1943-2597
Abstract
The k-nearest neighbor rule is one of the simplest and most attractive pattern classification algorithms. However, it faces serious challenges when patterns of different classes overlap in some regions in the feature space. In the past, many researchers have developed various methods to improve its performance. In this paper, we propose an improved evidence theoretic kNN algorithm which combines Dempster Shafer theory of evidence and k nearest neighbouring rule with distance metric based neighborhood. It is shown that the proposed algorithm significantly improves the performance of the k-nearest neighbor rule. In experiments this algorithm performed better than voting, distance weighted and extended k nearest neighbours algorithms with best k, and it achieved highest performance when number of neighbours considered is seven.
References
- Chavez, E., Navarro, G., Baeza-Yates, R., Marroquin, J. L. 2001 Searching in Metric Spaces, ACM Computer Surveys, Vol. 33:3, pp. 273-321.
- Cover, T. M. and Hart, P. E. 1967. Nearest neighbour pattern classification. IEEE Trans. Inform. Theory, IT-13, 21–27
- Cunningham, P., and Sarah Jane Delany, 2007: k-Nearest Neighbour Classifiers, Technical Report UCD-CSI-2007-4.
- Denoeux, T. 1995: A k-nearest neighbor classification rule based on Dempster-Shafer theory. IEEE Transactions on Systems, Man and Cybernetics:, 25, 804–813.
- Dudani, S. A. 1976. The distance-weighted k-nearest- neighbor rule. IEEE Trans.Syst. Man Cyber., 6, 325–327.
- Fix, E., and Hodges, J.L. 1951. Nonparametric discrimination: consistency properties, USAF School Aviation Medicine, Randolph Field, TX, Tech. Rep. 4.
- Pal, N.R., and Susmita Ghosh. 2001. Some Classification Algorithms Integrating Dempster–Shafer Theory of Evidence with the Rank Nearest Neighbor Rules, IEEE Transactions on Systems, Man, and Cybernetics— Part A: Systems And Applications, Vol. 31, PP 59-66.
- Shafer, G. 1976. A mathematical theory of evidence. Princeton University Press, Princeton, New Jersey.
- Smets, P. and Kennes, R. 1994. The transferable belief model. Artificial Intelligence, 66,191–234
- Wang, J., Neskovic, P., Cooper, L.N. 2007: Improving the Nearest Neighbor rule with a simple adaptive distance measure. Pattern Recognition 28, 207– 213.
- Wang, H., and David Bell. 2004. Extended k- Nearest Neighbours based on Evidence Theory, The Computer Journal, vol 47, pp 662–672
- Zouhal, L. M. and Denoeux, T. 1998. An evidence- theoretic k-nn rule with Parameter optimization.IEEE Transactions on Systems, Man and Cybernetics, 28,263–271.
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