Used by corporations, industry, and government to inform and
fuel everything from focused advertising to homeland security, data
mining can be a very useful tool across a wide range of
applications. Unfortunately, most books on the subject are designed
for the computer scientist and statistical illuminati and leave the
reader largely adrift in technical waters.
Revealing the lessons known to the seasoned expert, yet rarely
written down for the uninitiated, Practical Data Mining explains
the ins-and-outs of the detection, characterization, and
exploitation of actionable patterns in data. This working field
manual outlines the what, when, why, and how of data mining and
offers an easy-to-follow, six-step spiral process. Catering to IT
consultants, professional data analysts, and sophisticated data
owners, this systematic, yet informal treatment will help readers
answer questions, such as:
- What process model should I use to plan and execute a data
mining project?
- How is a quantitative business case developed and
assessed?
- What are the skills needed for different data mining
projects?
- How do I track and evaluate data mining projects?
- How do I choose the best data mining techniques?
Helping you avoid common mistakes, the book describes specific
genres of data mining practice. Most chapters contain one or more
case studies with detailed projects descriptions, methods used,
challenges encountered, and results obtained. The book includes
working checklists for each phase of the data mining process. Your
passport to successful technical and planning discussions with
management, senior scientists, and customers, these checklists lay
out the right questions to ask and the right points to make from an
insider's point of view.
Visit the book's webpage for access to additional
resources-including checklists, figures, PowerPoint slides, and a
small set of simple prototype data mining tools.
http: //www.celestech.com/PracticalDataMining
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