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A decision tree is a decision support recursive partitioning structure that uses a tree-like model of decisions and their possible consequences, including 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,[1] to help identify a strategy most likely to reach a goal, but are also a popular tool in machine learning.
- ^ von Winterfeldt, Detlof; Edwards, Ward (1986). "Decision trees". Decision Analysis and Behavioral Research. Cambridge University Press. pp. 63–89. ISBN 0-521-27304-8.