Classification by pairwise coupling
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
On the Learnability and Design of Output Codes for Multiclass Problems
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
Combining Labeled and Unlabeled Data for Text Classification with a Large Number of Categories
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
Reducing the classification cost of support vector classifiers through an ROC-based reject rule
Pattern Analysis & Applications
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Art of Error Correcting Coding
The Art of Error Correcting Coding
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Data-driven decomposition for multi-class classification
Pattern Recognition
Subclass Problem-Dependent Design for Error-Correcting Output Codes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Classification with a Reject Option using a Hinge Loss
The Journal of Machine Learning Research
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Dynamic multiple fault diagnosis: mathematical formulations and solution techniques
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Pattern Recognition Letters
On the Decoding Process in Ternary Error-Correcting Output Codes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A framework for multiclass reject in ECOC Classification systems
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Exploiting System Knowledge to Improve ECOC Reject Rules
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
To reject or not to reject: that is the question-an answer in caseof neural classifiers
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
On optimum recognition error and reject tradeoff
IEEE Transactions on Information Theory
A method for improving classification reliability of multilayer perceptrons
IEEE Transactions on Neural Networks
On the design of an ECOC-Compliant Genetic Algorithm
Pattern Recognition
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ECOC is a widely used and successful technique, which implements a multi-class classification system by decomposing the original problem into several two-class problems. In this paper, we study the possibility to provide ECOC systems with a tailored reject option carried out through different schemes that can be grouped under two different categories: an external and an internal approach. The first one is based on the reliability of the entire system output and does not require any change in its structure. The second scheme, instead, estimates the reliability of the internal dichotomizers and implies a slight modification in the decoding stage. Experimental results on popular benchmark data sets are reported to show the behavior of the different schemes.