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June 25, 2007 (Computerworld) -- This article is excerpted from Java Data Mining: Strategy, Standard and Practice, by Mark F. Hornick, Erik Marcad and Sunil Venkayala. Printed with permission from Morgan Kaufmann, a division of Elsevier. Copyright 2007.

As with any technology, the challenge to gaining proficiency is not being afraid to venture into the unknown. As Mark Twain noted, "the secret of getting ahead is getting started," and a strategy to get ahead with data mining is to start with small problems and data sets, learn some basic techniques and processes, and keep practicing.

This chapter introduces a small code example to give the reader a feel for the Java Data Mining (JDM) application programming interface (API) in the context of a specific business problem before going into more detailed examples in Parts II and III of this book. The business problem we address involves response modeling, as discussed in Chapter 2, for a fictitious company DMWhizz and its product, Gizmos.

Rather than dive right into the code, this chapter follows the CRISP-DM data mining process by first discussing the business understanding, data understanding and data preparation phases. Code is shown for modeling, and evaluation and deployment are discussed. Note that each process phase is not explored in depth, but enough to give the reader a feel for the phase.

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