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Erschienen in:
2008 | OriginalPaper | Buchkapitel
Fusers Based on Classifier Response and Discriminant Function – Comparative Study
verfasst von : Michal Wozniak, Konrad Jackowski
Erschienen in: Hybrid Artificial Intelligence Systems
Verlag: Springer Berlin Heidelberg
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The
Multiple Classifier Systems
are nowadays one of the most promising directions in pattern recognition. There are many methods of decision making by the ensemble of classifiers. The most popular are methods that have their origin in voting method, where the decision of the common classifier is a combination of individual classifiers’ decisions. This work presents methods of classifier combination, where neural networks plays a role of fuser block. Fusion on level of recognizer responses or values of their discriminant functions is applied. The qualities of proposed methods are evaluated via computer experiments on generated data and two benchmark databases.