Myriam Bounhas

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. Abstract Naive Bayesian Classifiers, which rely on independence hypotheses, together with a normality assumption to estimate densities for numerical data, are known for their simplicity and their effectiveness. However(More)
Naive Possibilistic Network Classifiers (NPNC) have been recently used to accomplish the classification task in presence of uncertainty. Because they are mainly based on possibility theory, they run into problems when they are faced with imperfection where the possibility theory is the most convenient tool to represent it. In this paper we investigate to(More)