Decision Trees
The concept describes one of the most used decision-making models, a decision tree, which explores all possible decisions and their consequences and allows for comparison of such alternatives in one single pane.
Technique Overview
Decision Trees Definition
A decision tree is an analytical tool for partitioning a dataset based on the relationships between a group of independent variables and a dependent variable (Coles and Rowley, 1995). It is a pictorial representation of the flow of events in a logical and time-sequenced manner so that the decision-maker can consider the probabilities of each outcome (Marsh, 1993). In other words, it is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, such as chance event outcomes, resource costs, and utility.
Decision Trees Description *
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Business Evidence
Strengths, weaknesses and examples of Decision Trees *
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Business Application
Implementation, success factors and measures of Decision Trees *
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Professional Tools
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Further Reading
Decision Trees web and print resources *
Decision Trees references (4 of up to 20) *
- Berson, A. and Smith, S.J. (2008) Data Warehousing, Data Mining, & OLAP. Tata McGraw-Hill.
- Breiman, L., Friedman, J.H., Olshen, R.A. and Stone, C.J. (1984) Classification and Regression Trees. Chapman and Hall.
- Brown, S.D. and Myles, A.J. (2009) Decision Tree Modeling in Classification. Comprehensive Chemometrics, Vol. 3, pp. 541-569.
- Buckley, J. and Dudley, T.J. (1999) How Gerber Used a Decision Tree in Strategic Decision-making. Graziadio Business Review, Vol. 2(3), pp. 1-6.
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