Handling uncertain labels in multiclass problems using belief decision trees
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چکیده
This paper investigates the induction of decision trees based on the theory of belief functions. This framework allows to handle training examples whose labeling is uncertain or imprecise. A former proposal to build decision trees for twoclass problems is extended to multiple classes. The method consists in combining trees obtained from various two-class coarsenings of the initial frame.
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Induction of decision trees from partially classified data using belief functions
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تاریخ انتشار 2002