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Teaching Decision Tree Classification Using Microsoft Excel

Listed author(s):
  • Kaan Ataman


    (Argyros School of Business and Economics, Chapman University, Orange, California 92866)

  • George Kulick


    (Le Moyne College, Syracuse, New York 13214)

  • Thaddeus Sim


    (Le Moyne College, Syracuse, New York 13214)

Registered author(s):

    Data mining is concerned with the extraction of useful patterns from data. With the collection, storage, and processing of data becoming easier and more affordable by the day, decision makers increasingly view data mining as an essential analytical tool. Unfortunately, data mining does not get as much attention in the OR/MS curriculum as other more popular areas such as linear programming and decision theory. In this paper, we discuss our experiences in teaching a popular data mining method (decision tree classification) in an undergraduate management science course, and we outline a procedure to implement the decision tree algorithm in Microsoft Excel.

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    Article provided by INFORMS in its journal INFORMS Transactions on Education.

    Volume (Year): 11 (2011)
    Issue (Month): 3 (May)
    Pages: 123-131

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    Handle: RePEc:inm:orited:v:11:y:2011:i:3:p:123-131
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