Adding Classes Online in Error Correcting Output Codes Framework

Sergio Escalera, David Masip, Eloi Puertas, Petia Radeva, Oriol Pujol

Abstract: 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.