Modeling

The Modeling phase is probably what you expect it to be—the phase where the modeling algorithms move to the forefront. In many ways, this is the easiest phase, as the algorithms do a lot of the work if you have done an excellent job on the prior phases and you've done a good job translating the business problem into a data mining problem. Despite the fact that the algorithms are doing the heavy lifting in this phase, it is generally considered the most intimidating; it is understandable why. There are an overwhelming number of algorithms to choose from. Even in a well-curated workbench such as Modeler, there are dozens of choices. Open source options such as R have hundreds of choices. While this book is not an algorithms guide, and even though it is impossible to offer a chapter on each algorithm, Chapter 9, Introduction to Modeling Options in IBM SPSS Modeler should be very helpful in understanding, at a high level, what options are available in Modeler. Also, in Chapter 10, Decision Tree Models we go through a thorough demonstration of one modeling technique, decision trees, to orient you to modeling in Modeler.

The four tasks in this phase are:

• Select modeling technique
• Generate test design
• Build model
• Assess model