Classifier fusion within the belief function framework using dependent combination rules

International audienceThe fusion of imperfect data within the framework of belief functions has been studied by many researchers over the past few years. Up to now, there are some proposed combination rules dealing with dependent information sources. Moreover, the choice of one rule among several alternatives is crucial but the criteria to be based on are still non clear. Thus, in this paper, we evaluate and compare some dependent combination rules for selecting the most efficient one under the framework of classifier fusion