DocumentCode
446037
Title
A comparative analysis of the performance of hybrid and non-hybrid multi-classifier systems
Author
Canuto, Anne M P ; De Souto, Marcilio C P ; Santos, Araken M. ; Bezerra, Valeria M S ; Mirelli, Sussany
Author_Institution
Dept. of Informatics & Appl. Math., Fed. Univ. of Rio Grande do Norte, Natal, Brazil
Volume
3
fYear
2005
fDate
31 July-4 Aug. 2005
Firstpage
1941
Abstract
This paper investigates the performance of some multi-classifier systems, focusing on the benefits that can be gained when integrating different types of classifiers (hybrid multi-classifier systems). An empirical evaluation shows that the integration of different types of classifiers can lead to an improvement in performance in some practical classification tasks.
Keywords
neural nets; pattern classification; classification task; hybrid multiclassifier system; Character recognition; Data analysis; Electronic mail; Face recognition; Informatics; Mathematics; Neural networks; Pattern recognition; Performance analysis; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Print_ISBN
0-7803-9048-2
Type
conf
DOI
10.1109/IJCNN.2005.1556177
Filename
1556177
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