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• W2290996932 abstract "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 identi- fies 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. Results on different multi-class data sets show the benefits of using the ensemble of classifiers when categorizing objects in images." @default.
• W2290996932 created "2016-06-24" @default.
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• W2290996932 date "2011-01-01" @default.
• W2290996932 modified "2023-10-17" @default.
• W2290996932 title "Chapter 2 Multi-class Classification in Image Analysis via Error-Correcting Output Codes" @default.
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