The resulting algorithm allows the processing of training data whose class membership is only partially specified in the form of a belief function. Experimental ...
Feb 28, 2000 · ... Induction of decision trees from partially classified data using belief functions. Oppgavens tekst: Most of the work on pattern classification ...
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A new tree-structured classifier based on the. Dempster-Shafer theory of evidence is presented. The entropy measure classically used to assess the impurity.
A new tree-structured classifier based on the Dempster-Shafer theory of evidence is presented. The entropy measure classically used to assess the impurity ...
A new tree-structured classifier based on the Dempster-Shafer theory of evidence is presented. The entropy measure classically used to assess the impurity ...
An algorithm for building decision trees in an uncertain environment will use the theory of belief functions in order to represent the uncertainty about the ...
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 ...
Decision tree classifiers are popular classification methods. In this paper, we extend to multi-class problems a decision tree method based on belief ...
Denoeux, M.S. Bjanger, Induction of decision trees from partially classified data using belief functions, in: IEEE Int. Conf. on Systems, Man and ...
Abstract Decision trees classifiers are popular classification methods. In this paper, we extend to multi-class problems a decision tree method based on ...