Finding Prototypes for Nearest Neighbor Classifiers

IEEE Transactions on Computers

Volumn C-23, Issue 11, 1974, Pages 1179-1184

  Chang, Chin Liang ^a,b  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

^b IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

Discriminant functions; generation of prototypes; minimal spanning tree algorithm; nearest neighbor classifiers; pattern recognition; piecewise linear classifiers; recognition rates; test sets; training sets

Indexed keywords

PATTERN RECOGNITION SYSTEMS;

EID: 0016127071     PISSN: 00189340     EISSN: None     Source Type: Journal    
DOI: 10.1109/T-C.1974.223827     Document Type: Article

References (9)

1. C. L. Chang, “Pattern recognition by piecewise linear discriminant functions,” IEEE Trans. Comput., vol. C-22, pp. 859–862, Sept. 1973.
2. T. M. Cover and P. E. Hart, “Nearest neighbor pattern classification,” IEEE Trans. Inform. Theory, vol. IT-13, pp. 21–27, Jan. 1967.
3. D. J. Croft, “Is computerized diagnosis possible?” Comput. Biomed. Res., vol. 5, pp. 351–367, 1972.
4. R. A. Fisher, “The use of multiple measurements in taxonomic problems,” Ann. Eugen., vol. 7, pp. 178–188, 1936.
5. P. E. Hart, “The condensed nearest neighbor rule,” IEEE Trans. Inform. Theory (Corresp.), pp. 515–516, May 1968.
6. W. S. Meisel, Computer-Oriented Approaches to Pattern Recog nition. New York: Academic, 1972.
7. R. C. Prim, “Shortest connection networks and some generalizations,” Bell Syst. Tech. J., pp. 1389–1401, Nov. 1957.
8. G. J. S. Ross, “Minimum spanning tree,” Appl. Statist., vol. 18, no. 1, pp. 103–104, 1969.
9. C. T. Zahn, “Graph-theoretical methods for detecting and describing Gestalt clusters,” IEEE Trans. Comput., vol. C-20, pp. 68–86, Jan. 1971.