Decision Trees

  • Robert C. Blattberg
  • Byung-Do Kim
  • Scott A. Neslin
Part of the International Series in Quantitative Marketing book series (ISQM, volume 18)


Decision trees are a very intuitive, easy-to-implement predictive modeling technique. They literally can be depicted as a tree — a sequence of criteria for classifying customers according to a metric such as likelihood of response. The pictorial representation of the tree makes it easy to apply and communicate. This chapter discusses the methods for creating the branches of the tree, deciding how many branches the tree should have and further details in constructing decision trees.


Decision Tree Root Node Internal Node Child Node Terminal Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Robert C. Blattberg
    • 1
    • 2
  • Byung-Do Kim
    • 3
  • Scott A. Neslin
    • 4
  1. 1.Kellogg School of ManagementNorthwestern UniversityEvanstonUSA
  2. 2.Tepper School of BusinessCarnegie-Mellon UniversityPittsburghUSA
  3. 3.Graduate School of BusinessSeoul National UniversitySeoulKorea
  4. 4.Tuck School of BusinessDartmouth CollegeHanoverUSA

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