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Partially supervised learning by a Credal EM approach

par Vannoorenberghe, Patrick;Smets, Philippe
Référence Lecture notes in computer science, 3571 LNAI, page (956-967)
Publication Publié, 2005

Article révisé par les pairs

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Résumé :

In this paper, we propose a Credal EM (CrEM) approach for partially supervised learning. The uncertainty is represented by belief functions as understood in the transferable belief model (TBM). This model relies on a non probabilistic formalism for representing and manipulating imprecise and uncertain information. We show how the EM algorithm can be applied within the TBM framework when applied for the classification of objects and when the learning set is imprecise (the actual class of each object is only known as belonging to a subset of classes), and/or uncertain (the knowledge about the actual class is represented by a probability function or by a belief function). © Springer-Verlag Berlin Heidelberg 2005.