Investigating The Fusion of Classifiers Designed Under Different Bayes Errors
We investigate a number of parameters commonly affecting the design of a multiple classifier system in order to find when fusing is most beneficial. We extend our previous investigation to the case where unequal classifiers are combined. Results indicate that Sum is not affected by this parameter, h...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
International Institute of Informatics and Cybernetics
2004-12-01
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Series: | Journal of Systemics, Cybernetics and Informatics |
Subjects: | |
Online Access: | http://www.iiisci.org/Journal/CV$/sci/pdfs/P658547.pdf
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