A merge-based condensing strategy for multiple prototype classifiers

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 32, Issue 5, 2002, Pages 662-668

  Mollineda, Ramón A ^a   Ferri, Francesc J ^b   Vidal, Enrique ^a  

^a INSTITUTO TECNOLÓGICO DE INFORMÁTICA   (Spain)

^b UNIVERSITY OF VALENCIA   (Spain)

Author keywords

Clustering; Condensing; Multiple prototypes; Nearest neighbors (NNs)

Indexed keywords

ALGORITHMS; ASYMPTOTIC STABILITY; COMPUTATIONAL GEOMETRY; KNOWLEDGE BASED SYSTEMS; OPTIMIZATION; SET THEORY;

GEOMETRIC CLUSTERS; GEOMETRIC PROPERTIES; HIERARCHICAL CLUSTERING FRAMEWORK; MULTIPLE PROTOTYPE CLASSIFIERS; NEAREST NEIGHBOR RULE;

HIERARCHICAL SYSTEMS;

EID: 0036790661     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2002.1033185     Document Type: Letter

References (20)

1. B. V. Dasarathy, Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques, B. V. Dasarathy, Ed: IEEE Comput. Soc. Press, 1991.
2. P. Devijver and J. Kittler, Pattern Recognition: A Statistical Approach. Englewood Cliffs, NJ: Prentice-Hall, 1982.
3. P. E. Hart, "The condensed nearest neighbor rule," IEEE Trans. Inform-Theory, vol. IT-14, pp. 515-516, May 1968.
4. B. V. Dasarathy, "Minimal consistent set (MCS) identification for optimal nearest neighbor decision systems design," IEEE Trans. Syst., Man, Cybern., vol. 24, pp. 511-517, Mar. 1994.
5. L. I. Kuncheva and J. C. Bezdek, "Nearest prototype classification: Clustering, genetic algorithms, or random search?," IEEE Trans. Syst., Man. Cybern. B, vol. 28, pp. 160-164, Feb. 1998.
6. C. L. Chang, "Finding prototypes for nearest neighbor classifiers," IEEE Trans. Comput., vol. C-23, pp. 1179-1184, Nov. 1974.
7. T. Kohonen, "The self-organizing map," Proc. IEEE, vol. 78, no. 9, pp. 1464-1480, 1990.
8. J. C. Bezdek, T. R. Reichherzer, G. S. Lim, and Y. Attikiouzel, "Multiple-prototype classifier design," IEEE Trans. Syst., Man, Cybern. B, vol. 28, pp. 67-79, Feb. 1998.
9. R. A. Mollineda, "Hierarchical agglomerative clustering for prototype selection and distance-based classification. use in cyclic strings," Ph.D. dissertation, Sch. Comput. Sci., Univ. Politècnica de València, València, Spain, 2001.
10. T. Kohonen, Self-Organizing Maps. New York: Springer-Verlag, 1995.
11. H. Yan, "Prototype optimization for nearest neighbor classifiers using a two-layer perceptron," Pattern Recognit., vol. 26, no. 2, pp. 317-324, 1993.
12. Y. S. Huang, K. Liu, and C. Y. Suen, "A new method of optimizing prototypes for nearest neighbor classifiers using a multilayer network," Pattern Recognit. Lett., vol. 16, no. 1, pp. 77-82, 1995.
13. F. Murtagh, "A survey of recent advances in hierarchical clustering algorithms," Comput. J., vol. 26, no. 4, pp. 354-359, 1983.
14. E. Anderson, "The IRISes of the Gaspe peninsula," in Proc. Bull. Amer. IRIS Soc., vol. 59, 1935, pp. 2-5.
15. T. Kohonen, "Statistical pattern recognition with neural networks: Benchmarking studies," in Proc. IJCNN, vol. I, San Diego, CA, 1988, pp. 61-68.
16. R. D. King, "Statlog Databases," Dept. Statist, Modeling Scie., Univ. of Strathclyde, Glasgow, U.K., 1992.
17. J. S. Sánchez, F. Pla, and F. J. Ferri, "Prototype selection for the nearest neighbor rule through proximity graphs," Pattern Recognit. Lett., vol. 18, no. 6, pp. 507-513, 1997.
18. D. L. Wilson, "Asymptotic properties of nearest neighbor rules using edited data," IEEE Trans. Syst., Man, Cybern., vol. SMC-2, pp. 408-421, 1972.
19. (1997) LVQ PAK: The learning vector quantization package. Helsinki Univ. Technol., Helsinki, Finland. [Online]. Available: http://www.cis.hu.fi/research/lvq_pak
20. A. Webb, Statistical Pattern Recognition. London, U.K.: E. Arnold, 1999.