A Pre-Pruning Method in Belief Decision Trees
نویسندگان
چکیده
The belief decision tree approach is a decision tree method adapted in order to handle uncertainty about the actual class of the objects in the training set. The uncertainty is represented by the Transferable Belief Model (TBM). We present two methods to build the tree. In order to reduce the size and the complexity of the induced tree, we present a pre-pruning tool related to the stopping criteria used during the development of the paths.
منابع مشابه
Pruning Method of Belief Decision Trees
The belief decision tree (BDT) approach is a decision tree in an uncertain environment where the uncertainty is represented through the Transferable Belief Model (TBM), one interpretation of the belief function theory. The uncertainty can appear either in the actual class of training objects or attribute values of objects to classify. In this paper, we develop a post-pruning method of belief de...
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