
This Article  
 
Share  
Bibliographic References  
Add to:  
Digg Furl Spurl Blink Simpy Del.icio.us Y!MyWeb  
Search  
 
ASCII Text  x  
Q. Xie, C.A. Laszlo, R.K. Ward, "Vector Quantization Technique for Nonparametric Classifier Design," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 12, pp. 13261330, December, 1993.  
BibTex  x  
@article{ 10.1109/34.250849, author = {Q. Xie and C.A. Laszlo and R.K. Ward}, title = {Vector Quantization Technique for Nonparametric Classifier Design}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {15}, number = {12}, issn = {01628828}, year = {1993}, pages = {13261330}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.250849}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  Vector Quantization Technique for Nonparametric Classifier Design IS  12 SN  01628828 SP1326 EP1330 EPD  13261330 A1  Q. Xie, A1  C.A. Laszlo, A1  R.K. Ward, PY  1993 KW  vector quantization; nonparametric classifier; design; knearest neighbour; data reduction rates; Parzen kernel classifier; condensing algorithm; approximation theory; data reduction; pattern recognition; vector quantisation VL  15 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
An effective data reduction technique based on vector quantization is introduced for nonparametric classifier design. Two new nonparametric classifiers are developed, and their performance is evaluated using various examples. The new methods maintain a classification accuracy that is competitive with that of classical methods but, at the same time, yields very high data reduction rates.
[1] K. Fukunaga,Introduction to Statistical Pattern Recognition. New York: Academic, 1972.
[2] J. Hand,Discrimination and Classification. New York: Wiley, 1981.
[3] J. W. V. Ness, "On the effects of dimension in discriminant analysis for unequal covariance populatins,"Technometrics, vol. 21, pp. 119127, 1979.
[4] J. W. V. Ness and C. Simpson, "On the effects of dimension in discriminant analysis,"Technometrics, vol. 18, pp. 175187, 1976.
[5] P. E. Hart, "The condensed nearest neighbor rule,"IEEE Trans. Inform. Theory, vol. IT14, pp. 515516, 1968.
[6] G. W. Gates, "The reduced nearest neighbor rule,"IEEE Trans. Inform. Theory, vol. IT18, pp. 431433, 1972.
[7] P. A. Devijver and J. Kittler, "On the edited nearest neighbor rule," inProc. 5th Int. Conf. Pattern Recogn., 1980, pp. 7280.
[8] K. Fukunaga and R. R. Hayes, "The reduced Parzen classifier,"IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI11, pp. 423425, Apr. 1989.
[9] K. Fukunaga and J. M. Mantock, "Nonparametric data reduction,"IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI6, pp. 115118, Jan. 1984.
[10] Y. Linde, A. Buzo, and R. M. Gray, "An algorithm for vector quantizer design,"IEEE Trans. Commun., vol. COM28, pp. 8495, Jan. 1980.
[11] T. Kohonen, "Learning vector quantization,"Neural Net., vol. 1, pp. 303, 1988, Supplement 1.
[12] T. Kohonen, G. Barna, and R. Chrisley, "Statistical pattern recognition with neural networks: Benchmarking studies," inProc. IEEE Int. Conf. Neural Networks, (San Diego), 1988, pp. I:6168.
[13] N. M. Nasrabadi and Y. Feng, "Vector quantization of images based upon the Kohonen selforganizing feature maps," inProc. IEEE Int. Conf. Neural Networks, San Diego, CA, 1988, pp. 11011108.
[14] A. Gersho, "Asymptotically optimal block quantization,"IEEE Trans. Inform. Theory, vol. IT25, p. 373, 1979.
[15] D. J. Hand,Kernel Discriminant Analysis. New York: Research Studies, 1982.