Difference between revisions of "Decision Trees"
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Latest revision as of 19:54, 27 August 2020
Decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. A decision tree combines the idea of a Probability tree with Expected value.
A decision tree consists of 3 types of nodes: 1. Decision nodes - commonly represented by squares 2. Chance nodes - represented by circles 3. End nodes - represented by triangles
