It is known that error-correcting output codes (ECOC) is a common way to model multiclass classification problems

in which the research of encoding based on data especially attracts attentions.In this paper

we proposed a method for learning error-correcting output codes with the help of a single layered perception neural network.To achieve this goal

the code elements of ECOC are mapped to the weights of network for the given decoding strategy

and an object function with the constrained weights used as a cost function of network.After the training

we can obtain a coding matrix including lots of subgroups of class.Experimental results on artificial data and UCI with logistic linear classifier (LOGLC) as the binary learner show that our scheme provides better performance of classification with shorter length of coding matrix than other state-of-the-art encoding strategies.