Floating search methods in feature selection
Pattern Recognition Letters
Inductive Learning Algorithms for Complex Systems Modeling
Inductive Learning Algorithms for Complex Systems Modeling
Using Error-Correcting Codes for Text Classification
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Stochastic Organization of Output Codes in Multiclass Learning Problems
Neural Computation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Forest Extension of Error Correcting Output Codes and Boosted Landmarks
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Sharing features: efficient boosting procedures for multiclass object detection
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Recoding Error-Correcting Output Codes
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Blurred Shape Model for binary and grey-level symbol recognition
Pattern Recognition Letters
Error-Correcting Ouput Codes Library
The Journal of Machine Learning Research
Sub-class error-correcting output codes
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Learning ECOC and dichotomizers jointly from data
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Thinned-ECOC ensemble based on sequential code shrinking
Expert Systems with Applications: An International Journal
Ensemble of binary learners for reliable text categorization with a reject option
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Learning compact class codes for fast inference in large multi class classification
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
On the design of an ECOC-Compliant Genetic Algorithm
Pattern Recognition
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The error correcting output codes (ECOC) technique is a useful way to extend any binary classifier to the multiclass case. The design of an ECOC matrix usually considers an a priori fixed number of dichotomizers. We argue that the selection and number of dichotomizers must depend on the performance of the ensemble code in relation to the problem domain. In this paper, we present a novel approach that improves the performance of any initial output coding by extending it in a sub-optimal way. The proposed strategy creates the new dichotomizers by minimizing the confusion matrix among classes guided by a validation subset. A weighted methodology is proposed to take into account the different relevance of each dichotomizer. As a result, overfitting is avoided and small codes with good generalization performance are obtained. In the decoding step, we introduce a new strategy that follows the principle that positions coded with the symbol zero should have small influence in the results. We compare our strategy to other well-known ECOC strategies on the UCI database, and the results show it represents a significant improvement.