Decision Tree

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Description of Decision Tree. Explanation.


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Definition Decision Tree. Description.

A Decision Tree (DT) is a form of inductive reasoning using boolean alternatives (yes/no or true/false) or questions with a limited number of options to examine various things, such as: new product development, research and development options, plant modernization programs.

Composition of a Decision Tree. Elements.

A DT is typically (but not per se) represented as a graphical diagram consisting of nodes and branches that depicts the anatomy of a (business) decision and the interplay between a present decision, chance events, competitors’ activities, and possible future decisions and their results.

A decision tree consists of 3 main types of nodes:

  • Decision Nodes - normally represented by squares.
  • Chance Nodes - commonly represented by circles.
  • End Nodes - typically represented by triangles.

Usages of Decision Trees. Applications.

DTs are commonly used in operations research to support decision making and to help identify a strategy most likely to reach a goal.

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Usage (application): Contingency Theory, Normative Decision Model, Situational Leadership Theory, Path-Goal Theory

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Usage (application): Decision Trees, ID2, Entropy, Prepruning, Postpruning, Error Propagation

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Compare also: Mind Mapping  |  Theory of Constraints  |  Feasibility Study  |  Centralization and Decentralization

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