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A multi-class classifier based on the Bradley-Terry model predicts the multi-class label of an input by combining the outputs from multiple binary classifiers, where the combination should be a priori designed as a code word matrix. According to this framework, the code word matrix was originally designed to consist of +1 and -1, and has later been extended to allow zero components. This extension...
Based on the framework of error-correcting output coding (ECOC), we formerly proposed a multi-class classification method in which mis-classification of each binary classifier is regarded as a bit inversion error based on a probabilistic model of the noisy channel. In this article, we propose a modification of the method, based on localized likelihood, to deal with the discrepancy of metric between...
In this article, we propose a new method of multi-class classification in the framework of error-correcting output coding (ECOC). Misclassification of each binary classifier is formulated as a bit inversion error with a probabilistic model for each class and dependence between binary classifiers is incorporated into our model, which makes a decoder, a type of Boltzmann machine. Experimental studies...
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