Editing Decision tree (section)

{{Short description|Decision support tool}}
{{About|decision trees in decision analysis|the use of the term in machine learning |Decision tree learning}}
{{Use dmy dates|date=April 2020}}
[[Image:Manual decision tree.jpg|right|thumb|Traditionally, decision trees have been created manually.]]
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A '''decision tree'''  is a [[decision support system|decision support]] recursive partitioning structure that uses a [[Tree (graph theory)|tree-like]] [[Causal model|model]] of decisions and their possible consequences, including [[probability|chance]] event outcomes, resource costs, and [[utility]]. It is one way to display an [[algorithm]] that only contains conditional control statements.

Decision trees are commonly used in [[operations research]], specifically in [[decision analysis]],<ref>{{cite book |first1=Detlof |last1=von Winterfeldt |first2=Ward |last2=Edwards |chapter=Decision trees |pages=63–89 |title=Decision Analysis and Behavioral Research |location= |publisher=Cambridge University Press |year=1986 |isbn=0-521-27304-8 }}</ref> to help identify a strategy most likely to reach a goal, but are also a popular tool in [[Decision tree learning|machine learning]].