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17th International Conference on Pattern Recognition (ICPR'04) - Volume 1
Product Approximation by Minimizing the Upper Bound of Bayes Error Rate for Bayesian Combination of Classifiers
Cambridge UK
August 23-August 26
ISBN: 0-7695-2128-2
ASCII Text
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Hee-Joong Kang, David Doermann, "Product Approximation by Minimizing the Upper Bound of Bayes Error Rate for Bayesian Combination of Classifiers," Pattern Recognition, International Conference on, vol. 1, pp. 252-255, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004.
 
 
BibTex
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@article{ 10.1109/ICPR.2004.1334071,
author = {Hee-Joong Kang and David Doermann},
title = {Product Approximation by Minimizing the Upper Bound of Bayes Error Rate for Bayesian Combination of Classifiers},
journal ={Pattern Recognition, International Conference on},
volume = {1},
year = {2004},
issn = {1051-4651},
pages = {252-255},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334071},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Product Approximation by Minimizing the Upper Bound of Bayes Error Rate for Bayesian Combination of Classifiers
SN - 1051-4651
SP252
EP255
A1 - Hee-Joong Kang,
A1 - David Doermann,
PY - 2004
KW - null
VL - 1
JA - Pattern Recognition, International Conference on
ER -
 
Hee-Joong Kang, Hansung University, Seoul, Korea
David Doermann, University of Maryland, College Park
In combining multiple classifiers using a Bayesian formalism, a high dimensional probability distribution is composed of a class and decisions of classifiers. In order to do product approximation of the probability distribution, the upper bound of Bayes error rate, bounded by the conditional entropy of a class and decisions, should be minimized. A second-order dependency-based product approximation is proposed in this paper by considering the second-order dependency between the class and decisions. The proposed method is evaluated by combining the classifiers recognizing unconstrained handwritten numerals.
Citation:
Hee-Joong Kang, David Doermann, "Product Approximation by Minimizing the Upper Bound of Bayes Error Rate for Bayesian Combination of Classifiers," icpr, vol. 1, pp.252-255, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004
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