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Fuzzy inductive learning: Principles and applications in data mining

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2 Author(s)
Bouchon-Meunier, B. ; LIP6, Univ. Pierre et Marie Curie-Paris 6, Paris, France ; Marsala, C.

Inductive learning is an efficient way to construct knowledge from the observation of a set of cases. It rises from the particular to the general and it provides a system with the capacity of finding by itself any useful knowledge to handle forthcoming cases. Given a set of observed cases (a so-called training set), an inductive learning algorithm is able to construct a more complex knowledge base. This paper focuses on one of the inductive learning algorithms that are most intensively used in data mining. This algorithm enables the construction of a fuzzy decision tree which represents a set of decision rules.

Published in:

Intelligent System and Knowledge Engineering, 2008. ISKE 2008. 3rd International Conference on  (Volume:1 )

Date of Conference:

17-19 Nov. 2008