loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
On the Reduction of the Nearest-Neighbor Variation for More Accurate Classification and Error Estimates
May 1998 (vol. 20 no. 5)
pp. 567-571
ASCII Text
x 
 
Abdelhamid Djouadi, "On the Reduction of the Nearest-Neighbor Variation for More Accurate Classification and Error Estimates," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 5, pp. 567-571, May, 1998.
 
 
BibTex
x
 
@article{ 10.1109/34.682188,
author = {Abdelhamid Djouadi},
title = {On the Reduction of the Nearest-Neighbor Variation for More Accurate Classification and Error Estimates},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {20},
number = {5},
issn = {0162-8828},
year = {1998},
pages = {567-571},
doi = {http://doi.ieeecomputersociety.org/10.1109/34.682188},
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 - On the Reduction of the Nearest-Neighbor Variation for More Accurate Classification and Error Estimates
IS - 5
SN - 0162-8828
SP567
EP571
EPD - 567-571
A1 - Abdelhamid Djouadi,
PY - 1998
KW - Nearest-neighbor risk
KW - nearest-neighbor classifier
KW - Bayes error
KW - asymptotic risk
KW - risk estimation.
VL - 20
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 

Abstract—In designing the nearest-neighbor (NN) classifier, a method is presented to produce a finite sample size risk close to the asymptotic one. It is based on an attempt to eliminate the first-order effects of the sample size, as well as all higher odd terms. This method uses the 2-NN rule without the rejection option and utilizes a polarization scheme. Simulation results are included as a means of verifying this analysis.

[1] 567 T.M. Cover and P. Hart, "Nearest Neighbor Pattern Classification," Proc. IEEE Trans. Information Theory, pp. 21-27, 1967.[2] T.A. Brown and J. Kolpitz, "The Weighted Nearest Neighbor Rule for Class Dependent Samples Sizes," IEEE Trans. Information Theory, vol. 25, pp. 617-619, Sept. 1979.[3] R.D. Short and K. Fukunaga, "A New Nearest Neighbor Distance Measure," Proc. IEEE Pattern Recognition, pp. 81-86,Miami Beach, Fla., Dec. 1980.[4] R. Short and K. Fukanaga, "The Optimal Distance Measure for Nearest Neighbor Classification," IEEE Trans. Information Theory, vol. 27, pp. 622-627, 1981.[5] K. Fukunaga and T. Flick, "An Optimal Global Nearest Neighbor Metric," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 6, no. 3, pp. 314-318, May 1984.[6] K. Fukunaga and T. Flick, "The 2-NN Rule for More Accurate Risk Estimation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 7, no. 1, pp. 107-111, Jan. 1985.[7] P.A. Devijver, "New Error Bounds With the Nearest Neighbor Rule," IEEE Trans. Information Theory, vol. 25, pp. 749-753, Nov. 1979.[8] R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis, chapter 4. New York: Wiley, 1973.

Index Terms:
Nearest-neighbor risk, nearest-neighbor classifier, Bayes error, asymptotic risk, risk estimation.
Citation:
Abdelhamid Djouadi, "On the Reduction of the Nearest-Neighbor Variation for More Accurate Classification and Error Estimates," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 5, pp. 567-571, May 1998, doi:10.1109/34.682188
Usage of this product signifies your acceptance of the Terms of Use.