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Construction of forest of decision trees method is a popular tool in machine learning because of its good performances in terms of classification power as well as in computational cost. In this paper, we address two problems. The first one concerns the interpretability of a forest. Indeed, comparing to a single decision tree, a forest loose its ability to be easily understandable by an end-user. The...
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