Fuzzy Inductive Learning:Principles and Applications in Data Mining

摘要：

Inductive learning is an efficient way to construct knowl-edge from the observation of a set of cases.It rises from theparticular to the general and it provides a system with thecapacity of finding by itself any useful knowledge to han-die forthcoming cases.Given a set of observed cases (aso-called training set),an inductive learning algorithm isable to construct a more complex knowledge base.This pa-per focuses on one of the inductive learning algorithms thatare most intensively used in data mining.This algorithmenables the construction of a fuzzy decision tree which rep-resents a set of decision rules.

作者: Bernadette Bouchon-Meunier Christophe Marsala

作者单位: Universite Pierre et Marie Curie-Paris6,CNRS,UMR7606,LIP6,104 av.Du President Kennedy,Paris,F-75016,France.

会议类型: 国际会议

会议名称: 2008 3rd International Conference on Intelligent System and Knowledge Engineering(第三届智能系统与知识工程国际会议)(ISKE 2008)

会议地点: 厦门

会议语种:英文

页码: 1-4

在线出版日期: 2008-11-17（万方平台首次上网日期，不代表论文的发表时间）