An adaptive k-nearest neighbor algorithm

Proceedings - 2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

Volumn 1, Issue , 2010, Pages 91-94

  Sun, Shiliang ^a   Huang, Rongqing ^a  

^a EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

Adaptive k nearest neighbor algorithm (AdaNN); K nearest neighbor algorithm (kNN); Nearest neighbors; Pattern classification

Indexed keywords

CLASS LABELS; DATA SETS; K NEAREST NEIGHBOR ALGORITHM; K-NEAREST NEIGHBOR ALGORITHM (KNN); K-NN ALGORITHM; NEAREST NEIGHBORS; PATTERN CLASSIFICATION; TEST EXAMPLES; TRAINING EXAMPLE; TRAINING SETS;

FUZZY SETS; OPTIMIZATION;

ALGORITHMS;

EID: 78649309309     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FSKD.2010.5569740     Document Type: Conference Paper

References (16)

1. Y. Yang, "An evaluation of statistical approaches to text categorization," Information Retrivel 1, 1999, pp. 69-90.
2. T. Joachims, F. Informatik, and L. Viii, "Text categorization with support vector machines: learning with many relevant features," The 10th European Conference on Machine Learning, Springer, New York, 1998, pp. 137-142.
3. N. Japkowicz, "Learning from imbalanced data sets: a comparison of various strategies," AAAI workshop on learning from imbalanced data sets, 2000, pp. 10-15.
4. S. Tan, "Neighbor-weighted k-nearest neighbor for unbalanced text corpus," Expert Systems with Applications, vol. 28, 2005, pp. 667-671.
5. R.O. Duda and P.E. Hart, "Pattern classification and scene analysis," John Wiley & Sons, New York, 1973.
6. S.A. Dudani, "The distance-weighted k-nearest neighbor rule," IEEE Transactions on Systems, Man and Cybernetics, vol. 6, 1976, pp. 325-327.
7. B. Li, S. Yu and Q. Lu, "An improved k-nearest neighbor algorithm for text categorization," Proceedings of the 20th International Conference on Computer Processing of Oriental Languages, China: Shenyang, 2003.
8. S.L. Sun, "Ensembles of feature subspaces for object detection," Lecture Notes in Computer Science, vol. 5552, 2009, pp. 996-1004.
9. Y. Zeng, Y. Yang and L. Zhao, "Pseudo nearest neighbor rule for pattern classification," Expert Systems with Applications, vol. 36, 2009, pp.3587-3595.
10. S. Belongie, J. Malik and J. Puzicha, "Shape matching and object recognition using shape contexts," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 24(4), 2002, pp. 509-522.
11. P.Y. Simard, Y. LeCun and J. Decker, "Efficient pattern recognition using a new transformation distance," In Advances in Neural Information Processing Systems, vol. 6, 1993, pp. 50-58.
12. N. Japkowicz, "Learning from imbalanced data sets: a comparison of various strategies," AAAI Press, 2000, pp. 10-15.
13. E. Achtert, H. Kriegel, P. Kröger, M. Renz and A. Zfle, "Reverse k-nearest neighbor search in dynamic and general metric databases," Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, vol. 360, 2009, pp. 886-897.
14. T. Hastie and R. Tibshirani, "Discriminant adaptive nearest neighbor classification," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, 1996, pp. 607-616.
15. K.Q. Weinberger and L.K. Saul, "Distance metric learning for large margin nearest neighbor classification," The Journal of Machine Learning Research, vol. 10, 2009, pp. 207-244.
16. K. Mouratidis, D. Papadias and M. Hadjieleftheriou, "Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring," Proceedings of the 2005 ACM SIGMOD international conference on Management of data, 2005, pp. 634-645.