Design of reject rules for ECOC classification systems

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.