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Chapter 36: Fuzzy Decision Trees
Inductive decision trees were first introduced in 1963 with the concept learning system framework. Since then, they have continued to be developed and applied. The structure of a decision tree starts with a root decision node, from which all branches originate. A branch is a series of nodes where decisions are made at each node, enabling progression through (down) the tree. A progression stops at a leaf node, where a decision classification is given.
As with many data analysis techniques (e.g. traditional regression models), decision trees have been developed within a fuzzy environment. For example, the well-known decision tree method ID3 was developed to include fuzzy entropy measures. The fuzzy decision tree method was introduced by Yuan [Page 122]and Shaw (1995) to ...