Combining classifiers based on minimization of a Bayes error rate

Hee Joong Kang, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Citations (Scopus)

Abstract

In order to raise a class discrimination power by combining multiple classifiers, the upper bound of a Bayes error rate bounded by the conditional entropy of a class variable and decision variables should be minimized. Wang and Wong (1979) proposed a tree dependence approximation scheme of a high order probability distribution composed of those variables, based on minimizing the upper bound. In addition to that, this paper presents an extended approximation scheme dealing with higher order dependency. Multiple classifiers recognizing unconstrained handwritten numerals were combined by the proposed approximation scheme based on the minimization of the Bayes error rate, and the high recognition rates were obtained by them.

Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Document Analysis and Recognition, ICDAR 1999
PublisherIEEE Computer Society
Pages398-401
Number of pages4
ISBN (Electronic)0769503187
DOIs
Publication statusPublished - 1999 Jan 1
Event5th International Conference on Document Analysis and Recognition, ICDAR 1999 - Bangalore, India
Duration: 1999 Sep 201999 Sep 22

Other

Other5th International Conference on Document Analysis and Recognition, ICDAR 1999
CountryIndia
CityBangalore
Period99/9/2099/9/22

Fingerprint

Classifiers
Probability distributions
Entropy

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Kang, H. J., & Lee, S. W. (1999). Combining classifiers based on minimization of a Bayes error rate. In Proceedings of the 5th International Conference on Document Analysis and Recognition, ICDAR 1999 (pp. 398-401). [791808] IEEE Computer Society. https://doi.org/10.1109/ICDAR.1999.791808

Combining classifiers based on minimization of a Bayes error rate. / Kang, Hee Joong; Lee, Seong Whan.

Proceedings of the 5th International Conference on Document Analysis and Recognition, ICDAR 1999. IEEE Computer Society, 1999. p. 398-401 791808.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kang, HJ & Lee, SW 1999, Combining classifiers based on minimization of a Bayes error rate. in Proceedings of the 5th International Conference on Document Analysis and Recognition, ICDAR 1999., 791808, IEEE Computer Society, pp. 398-401, 5th International Conference on Document Analysis and Recognition, ICDAR 1999, Bangalore, India, 99/9/20. https://doi.org/10.1109/ICDAR.1999.791808
Kang HJ, Lee SW. Combining classifiers based on minimization of a Bayes error rate. In Proceedings of the 5th International Conference on Document Analysis and Recognition, ICDAR 1999. IEEE Computer Society. 1999. p. 398-401. 791808 https://doi.org/10.1109/ICDAR.1999.791808
Kang, Hee Joong ; Lee, Seong Whan. / Combining classifiers based on minimization of a Bayes error rate. Proceedings of the 5th International Conference on Document Analysis and Recognition, ICDAR 1999. IEEE Computer Society, 1999. pp. 398-401
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