Data Mining with Microsoft® SQL Server® 2008

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 chapter

• Chapter7.bak—A SQL Server 2008 database backup of the tables used in this chapter

• Chapter7.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. ...