Handwritten Symbol Recognition by a Boosted Blurred Shape Model with Error Correction
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Traffic sign recognition system with β -correction
Machine Vision and Applications
Decoding of ternary error correcting output codes
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Minimal design of error-correcting output codes
Pattern Recognition Letters
Error-correcting output codes based ensemble feature extraction
Pattern Recognition
Adaptive error-correcting output codes
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
On the design of an ECOC-Compliant Genetic Algorithm
Pattern Recognition
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Error correcting output codes (ECOC) represent a classification technique that allows a successful extension of binary classifiers to address the multiclass problem. In this paper, we propose a novel technique called ECOC-ONE to improve an initial ECOC configuration by including new dichotomies guided by the confusion matrix over exclusive training subsets. In this way, the initial coding represented by an optimal decision tree is extended adding binary classifiers forming a network. Since not all dichotomies have the same relevance, a weighted methodology is included. Moreover, to decode we introduce a new distance to attenuate the error accumulated by zeros in the ECOCONE matrix. We compare our strategy to other well-known ECOC coding strategies on the UCI data set achieving very promising results.