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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.
Multiple classifiers, multiclass classification, visual object recognition.

J. Vitri?, P. Radeva and O. Pujol, "Discriminant ECOC: A Heuristic Method for Application Dependent Design of Error Correcting Output Codes," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 28, no. , pp. 1007-1012, 2006.
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