Aiming at reducing misclassification costs

this paper studies the design of reject options for ECOC multi-classification based on its properties.The first level of reject option is constructed in the process of bipartitions to recognize an instance whose real labels does not belong to the meta-subclasses.Meanwhile

the second reject rule is presented in the dichotomizers based on posterior probabilities and cost matrix to make the minimum-risk Bayesian decision.Finally

different decoding strategies are analysed according to different reject output.The relationship between the number of rejected positions and the minimum Hamming distance of matrix is discussed.The two-stage reject rule makes the ECOC multi-classification with rejection come true and reduce the misclassification error and costs.