Accuracy/diversity and ensemble MLP classifier design
Windeatt, T (2006) Accuracy/diversity and ensemble MLP classifier design IEEE TRANSACTIONS ON NEURAL NETWORKS, 17 (5). pp. 1194-1211.
windeatt_transnndbl3.pdf - Accepted version Manuscript
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|Divisions :||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Date :||1 September 2006|
|Identification Number :||https://doi.org/10.1109/TNN.2006.875979|
|Uncontrolled Keywords :||Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, Hardware & Architecture, Computer Science, Theory & Methods, Engineering, Electrical & Electronic, Computer Science, Engineering, Boolean, diversity, error-correcting output coding (ECOC), face identification, multiple classifiers, RBF NEURAL-NETWORKS, FACE RECOGNITION, OUTPUT CODES, ACCURACY, ERROR|
|Related URLs :|
|Additional Information :||
Copyright 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
|Depositing User :||Symplectic Elements|
|Date Deposited :||13 Jan 2012 12:00|
|Last Modified :||17 Jan 2015 14:45|
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