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This paper extends the decision tree technique to an uncertain environment where the uncertainty is represented by belief functions as interpreted in the Transferable Belief Model (TBM). This so-called belief decision tree is a new classification method adapted to uncertain data. We will be concerned with the construction of the belief decision tree from a(More)
In this paper, we study the notion of marginal independence between two sets of variables when uncertainty is expressed by belief functions as understood in the context of the transferable belief model. We define the concepts of non-interactivity and irrelevance, that are not equivalent. Doxastic independence for belief functions is defined as irrelevance(More)
In the companion paper (Ben Yaghlane, Smets, & Mellouli, 2000a), we have enhanced the distinction between non-interactivity and doxastic independence in the context of the transferable belief model. The first corresponds to decompositionality of the belief function, whereas the second is defined as irrelevance preserved under Dempster's rule of combination.(More)