Multi-class Classification in Image Analysis Via Error-Correcting Output Codes
نویسندگان
چکیده
A common way to model multi-class classification problems is by means of Error-Correcting Output Codes (ECOC). Given a multi-class problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem. A classification decision is obtained by assigning the label of the class with the closest code. In this paper, we overview the state-of-the-art on ECOC designs and test them in real applications. Sergio Escalera Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Gran Via de les Corts Catalanes 585, 08007, Barcelona, Spain Computer Vision Center, Campus UAB, Edifici O, 08193, Bellaterra, Spain e-mail: [email protected] David M. J. Tax Information and Communication Theory (ICT) Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, PO Box 5031, 2600 GA, Delft, The Netherlands e-mail: [email protected] Oriol Pujol Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Gran Via de les Corts Catalanes 585, 08007, Barcelona, Spain Computer Vision Center, Campus UAB, Edifici O, 08193, Bellaterra, Spain e-mail: [email protected] Petia Radeva Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Gran Via de les Corts Catalanes 585, 08007, Barcelona, Spain Computer Vision Center, Campus UAB, Edifici O, 08193, Bellaterra, Spain e-mail: [email protected] Robert P. W. Duin Information and Communication Theory (ICT) Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, PO Box 5031, 2600 GA, Delft, The Netherlands e-mail: [email protected]
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