Using SAS Enterprise Miner, this example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements other business intelligence applications such as OLAP cubes; in addition, it explains other data mining approaches, like regression, cluster analysis, and neural networks. The book contains examples that illustrate how various aspects of decision trees are constructed, how they operate, how to interpret them, and how to use them in a range of predictive and descriptive applications. Many of the examples are drawn from purchase behavior, risk assessment, and business-to-business marketing. The target audience for this book includes analysts who already have an introductory understanding of data mining and who want to benefit from a more advanced, in-depth look at the theory and methods of a decision-tree approach to data mining and business intelligence.
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