Discriminant ECOC : a heuristic method for application dependent design of error correcting output codes

We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the part...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 28(2006), 6 vom: 06. Juni, Seite 1007-12
1. Verfasser: Pujol, Oriol (VerfasserIn)
Weitere Verfasser: Radeva, Petia, Vitrià, Jordi
Format: Aufsatz
Sprache:English
Veröffentlicht: 2006
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Evaluation Study Journal Article Research Support, Non-U.S. Gov't
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520 |a We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result, a compact matrix with high discrimination power is obtained. Our method is validated using the UCI database and applied to a real problem, the classification of traffic sign images 
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