Handbook of Statistical Analysis and Data Mining Applications (Hardcover)

~ Robert Nisbet (Author), John Elder IV (Author), Gary Miner (Author)

Editorial Reviews

Review

"Great introduction to the real-world process of data mining. The overviews, practical advise, tutorials, and extra CD material make this book an invaluable resource for both new and experienced data miners."

- Karl Rexer, PhD (President & Founder of Rexer Analytics, Boston, Massachusetts)


If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource. To put it lightly, if this book isn't on your shelf, you're not a data miner.

- Eric Siegel, Ph.D., President, Prediction Impact, Inc. and Founding Chair, Predictive Analytics World

Data mining practitioners, here is your bible, the complete "driver's manual" for data mining. From starting the engine to handling the curves, this book covers the gamut of data mining techniques - including predictive analytics and text mining - illustrating how to achieve maximal value across business, scientific, engineering and medical applications. What are the best practices through each phase of a data mining project? How can you avoid the most treacherous pitfalls? The answers are in here.

Going beyond its responsibility as a reference book, this resource also provides detailed tutorials with step-by-step instructions to drive established data mining software tools across real world applications. This way, newcomers start their engines immediately and experience hands-on success.

If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource. To put it lightly, if this book isn't on your shelf, you're not a data miner.

- Eric Siegel, Ph.D., President, Prediction Impact, Inc. and Founding Chair, Predictive Analytics World

"Great introduction to the real-world process of data mining. The overviews, practical advise, tutorials, and extra CD material make this book an invaluable resource for both new and experienced data miners."

-- Karl Rexer, PhD (President & Founder of Rexer Analytics, Boston, Massachusetts)

Data mining practitioners, here is your bible, the complete "driver's manual" for data mining. From starting the engine to handling the curves, this book covers the gamut of data mining techniques - including predictive analytics and text mining - illustrating how to achieve maximal value across business, scientific, engineering and medical applications. What are the best practices through each phase of a data mining project? How can you avoid the most treacherous pitfalls? The answers are in here.

Going beyond its responsibility as a reference book, this resource also provides detailed tutorials with step-by-step instructions to drive established data mining software tools across real world applications. This way, newcomers start their engines immediately and experience hands-on success.

If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource. To put it lightly, if this book isn't on your shelf, you're not a data miner.

- Eric Siegel, Ph.D., President, Prediction Impact, Inc. and Founding Chair, Predictive Analytics World

"Great introduction to the real-world process of data mining. The overviews, practical advise, tutorials, and extra CD material make this book an invaluable resource for both new and experienced data miners."

--Karl Rexer, PhD (President & Founder of Rexer Analytics, Boston, Massachusetts)

Book Description

The essential professional reference for data mining applications and statistical analysis.

See all Editorial Reviews

Product Details

• Hardcover: 864 pages
• Publisher: Academic Press; Har/DVD edition (June 5, 2009)
• Language: English
• ISBN-10: 0123747651
• ISBN-13: 978-0123747655
• Product Dimensions: 9.3 x 7.8 x 1.5 inches
• Shipping Weight: 3.4 pounds (View shipping rates and policies)
• Average Customer Review: 4.7 out of 5 stars  See all reviews (14 customer reviews)
• Amazon.com Sales Rank: #32,701 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

17 of 17 people found the following review helpful:

5.0 out of 5 stars The top data mining text on the market, June 18, 2009

By	Joseph Hilbe (Florence, AZ United States) - See all my reviews (REAL NAME)

The "Handbook of Statistical Analysis & Data Mining Applications" is the finest book I have seen on the subject. It is not only a beautifully crafted book, with numerous color graphs, chart, tables, and screen shots, but the statistical discussion is both clear and comprehensive.

The text does not use only one statistical data mining application to display examples, but provides a rather thorough training in the use of both SAS-Enterprise Miner and STATISTICA Data Miner. A section on SPSS Clementine is also provided, giving comparisons between the various packages. Also employed are STATISTICA's C&RT, CHAID, MARSpline, and other data mining and graphical analytic tools.

The text does not burden the typical data mining researcher with the internals of how the various tools work. It is therefore not steeped in equations. Some are to be found, of course, but the emphasis is on understanding the concepts involved and on how to apply these concepts to real data - which is provided to the reader in terms of data tutorials. Specialized datasets have been prepared by both authors and outside experts in various areas of inquiry ranging from entertainment, financial, engineering, clinical psychology, dentistry, demographics, medical informatics, meteorology, astronomy, and more. Each tutorial is associated with data stored on either the associated CD that comes with the book, or which can be downloaded from a companion web site. Worked out examples of how to use data mining techniques on such data is provided to help the reader gain a solid feel for the data mining enterprise. The final third of the book is devoted to a partial selection of the available tutorials. The two earlier chapters demonstrate how to use data mining software for the analysis of data.

I highly recommend this work to anyone having an interest in data mining. I might also add that the Amazon price of $72.37 is truly excellent for an 864 page academic text, having full color tables and screen shots on some one-third of the pages, plus a CD. A bargain indeed.

8 of 8 people found the following review helpful:

5.0 out of 5 stars Long Overdue, July 12, 2009

By	Colleen McCue (Virginia, United States) - See all my reviews (REAL NAME)

Rarely do authors succeed in writing THE comprehensive guide to anything, particularly when the subject matter is as complex, multifaceted and rapidly changing as the field of data mining. The Handbook of Statistical Analysis & Data Mining Applications far exceeds that worthy goal. The text is well organized, thoughtfully written and intuitive. The authors' comfortable style and examples from their own experience make even the most opaque concepts understandable and accessible. By following the CRISP-DM model and incorporating screen shots from the leading data mining platforms, the authors have written an invaluable text that incorporates both industry best practices and best-in-breed technology. Moreover, the math and science behind the concepts and methods are accurate and well-referenced; something missing in the junk science that so frequently passes for "advanced analytics." In successfully integrating these features, the Handbook excels as both a comprehensive teaching text and easy reference that will be used frequently by students and professionals alike. The Handbook of Statistical Analysis & Data Mining Applications is long overdue and certain to become THE comprehensive guide and a classic in our field.

8 of 8 people found the following review helpful:

5.0 out of 5 stars I really liked this book, June 27, 2009

By	Anonymous "Anonymous" (Nunya, USA (business address)) - See all my reviews

I had experience with many of the statistical tools that fall under the heading of data mining. There are good books on GAMs and so on. What I like about this book is that it embeds those methods in a broader context, that of the philosophy and structure of data mining writ large, especially as the methods are used in the corporate world. To me, it was really helpful in thinking like a data miner, especially as it involves the mix of science and art.

I also had no experience with Statistica Data Miner but have been very impressed with the program relative to those that are less well documented (WEKA) and too darned expensive (SAS EM)

The richness of the examples is so helpful.