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We address here the problem of supervised classification using belief functions. In particular, we study the combination of non-independent sources of information. In a companion paper, we showed that the cautious rule of combination may be best suited than the widely used Dempsterpsilas Rule to combine classifiers in the case of real data. Then, we considered combination rules intermediate between...
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