• Summary
  • Contents
  • Subject index

A must-have reference resource for qualitative management researchers, this dictionary contains over 90 entries covering the fundamentals of qualitative methodologies; covering both analysis and implementation. Each entry gives an introduction to the topic, lists the key relevant features, gives a worked example, a concise summary and a selection of further reading suggestions. It is suitable for researchers and academics who need a handy and quick point of reference.

Fuzzy Decision Trees
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 and Shaw (1995) to ...

  • Loading...
locked icon

Sign in to access this content

Get a 30 day FREE TRIAL

  • Watch videos from a variety of sources bringing classroom topics to life
  • Read modern, diverse business cases
  • Explore hundreds of books and reference titles