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Fuzzy Decision Trees
Fuzzy decision trees
Introduction

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 and Shaw (1995) to ...

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