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.

• Type: Conference
• Year: 2010
• Where: ICPR
• Authors: Sergio Escalera, David Masip, Eloi Puertas, Petia Radeva, Oriol Pujol
• Keywords: Base Classifier, Computer Vision, Error Correcting Output, ICPR 2010, Online Learning Scenario