Sergio Escalera, D. Masip, Eloi Puertas, P. Radeva, O. Pujol
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Adding Classes Online in Error Correcting Output Codes Framework
This article proposes a general extension of the Error Correcting Output Codes (ECOC) framework to the online learning scenario. As a result, the final classifier handles the addition of new classes independently of the base classifier used. Validation on UCI database and two real machine vision applications show that the online problem-dependent ECOC proposal provides a feasible and robust way for handling new classes using any base classifier.
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