Chapter 7. Microsoft Decision Trees Algorithm
Put yourself in the place of a loan officer at a bank. A young couple walks in to request a loan. Young, you think—not a good sign. You talk to them. They're married, and that's a plus. He's worked the same job for three years. Job stability is another good sign. A look at their credit reports shows they've missed three payments in the last 12 months—a big negative. From your experience, you've created a tree in your mind that allows you to determine how you rank each loan application. The question remains: Does this couple get the loan? A decision tree can help you solve this puzzle, as you'll see in this chapter.
In this chapter, you will learn about the following:
Using the Microsoft Decision Trees algorithm
Interpreting the tree model content
Understanding the principles of the Microsoft Decision Trees algorithm
You can find the associated files for this chapter in the file Chapter7.zip
at this book's companion website (www.wiley.com/go/data_mining_SQL_2008
). Chapter7.zip
includes the following files
Chapter7.abf
—An Analysis Services 2008 backup of the Analysis Services database used in this chapterChapter7.bak
—A SQL Server 2008 database backup of the tables used in this chapterChapter7.dmx
—A DMX query file containing the query listings in this chapter
Introducing Decision Trees
The decision tree is probably the most popular data mining technique because of fast training performance, a high degree of accuracy, and easily understandable patterns. ...
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