Database Reference
In-Depth Information
CHAPTER TEN:
DECISION TREES
CONTEXT AND PERSPECTIVE
Richard works for a large online retailer. His company is launching a next-generation eReader
soon, and they want to maximize the effectiveness of their marketing. They have many customers,
some of whom purchased one of the company's previous generation digital readers. Richard has
noticed that certain types of people were the most anxious to get the previous generation device,
while other folks seemed to content to wait to buy the electronic gadget later. He's wondering
what makes some people motivated to buy something as soon as it comes out, while others are less
driven to have the product.
Richard's employer helps to drive the sales of its new eReader by offering specific products and
services for the eReader through its massive web site—for example, eReader owners can use the
company's web site to buy digital magazines, newspapers, books, music, and so forth. The
company also sells thousands of other types of media, such as traditional printed topics and
electronics of every kind. Richard believes that by mining the customers' data regarding general
consumer behaviors on the web site, he'll be able to figure out which customers will buy the new
eReader early, which ones will buy next, and which ones will buy later on. He hopes that by
predicting when a customer will be ready to buy the next-gen eReader, he'll be able to time his
target marketing to the people most ready to respond to advertisements and promotions.
LEARNING OBJECTIVES
After completing the reading and exercises in this chapter, you should be able to:
Explain what decision trees are, how they are used and the benefits of using them.
Recognize the necessary format for data in order to perform predictive decision tree
mining.
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