Shaping the Error-Reject Curve of Error Correcting Output Coding Systems
A common approach in many classification tasks consists in reducing the costs by turning as many errors as possible into rejects. This can be accomplished by introducing a reject rule which, working on the reliability of the decision, aims at increasing the performance of the classification system. When facing multiclass classification, Error Correcting Output Coding is a diffused and successful technique to implement a system by decomposing the original problem into a set of two class problems. The novelty in this paper is to consider different levels where the reject can be applied in the ECOC systems. A study for the behavior of such rules in terms of Error-Reject curves is also proposed and tested on several benchmark datasets.
KeywordsError-Reject Curve reject option multiclass problem Error Correcting Output Coding
- 2.Asuncion, A., Newman, D.J.: UCI machine learning repository (2007)Google Scholar
- 8.Joachims, T.: Making large-scale SVM learning practical. In: Schölkopf, B., Burges, C., Smola, A. (eds.) Advances in Kernel Methods - Support Vector Learning, ch. 11. MIT Press, Cambridge (1999)Google Scholar
- 10.Simeone, P., Marrocco, C., Tortorella, F.: Exploiting system knowledge to improve ecoc reject rules. In: International Conference on Pattern Recognition, pp. 4340–4343. IEEE Computer Society, Los Alamitos (2010)Google Scholar