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Handbook of Statistical Analysis and Data Mining Applications Hardcover – June 5, 2009

ISBN-13: 978-0123747655 ISBN-10: 0123747651 Edition: 1st

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Product Details

  • Hardcover: 864 pages
  • Publisher: Academic Press; 1 edition (June 5, 2009)
  • Language: English
  • ISBN-10: 0123747651
  • ISBN-13: 978-0123747655
  • Product Dimensions: 1.5 x 7.5 x 9.2 inches
  • Shipping Weight: 3.4 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (33 customer reviews)
  • Amazon Best Sellers Rank: #185,717 in Books (See Top 100 in Books)

Editorial Reviews

Review

"I strongly resonated to the Top 10 Data Mining mistakes....  There is a wealth of material in this handbook that will repay study."

- Peter Lachenbruch, Oregon State U., Past President, American Statistical Society (from Foreword 1)

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)

... a valuable resource... The book's straightforward style--it presents intuitive explanations and avoids rigorous mathematical formulations--makes difficult concepts accessible to a broad audience.
-ACM Computing Reviews


"...an exceptional book that should be on every data miner's bookshelf, or better yet, found lying open next to the computer."

Dean Abbott, Abbott Analytics --from Foreword 2

"...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 advice, 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)

From the Back Cover

Tutorials employ leading software tools including STATISTICA Data Miner, SPSS Clementine, and SAS Enterprise Miner -- and show practitioners how to solve real-world data mining challenges in a wide variety of fields, including sales, medical diagnosis, finance, aviation engineering, marketing, banking, pharmaceutical discovery, industrial control, weather forecasting, clinical psychology, ecology, astronomy, and social networks.

This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build practical solutions.  Using the methods of this book produces new KNOWLEDGE that facilitates DECISIONS which lead to ACTIONS that result in SUCCESS.


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Customer Reviews

It is very well written and easy to follow.
Abdollah Haghighi
The "Handbook of Statistical Analysis & Data Mining Applications" is the finest book I have seen on the subject.
Joseph Hilbe
I especially appreciate the practical application examples contained in the book.
Stuart M. Rodgers

Most Helpful Customer Reviews

63 of 67 people found the following review helpful By James on June 2, 2010
Format: Hardcover Verified Purchase
This book is for practitioners, not for those seeking a deeper understanding of data mining. It both makes and delivers on that claim. All major data mining topics are covered, though in a necessarily shallow manner in keeping with the book's goal of getting past the theory and moving to the practice.

Oddly, the very start of the book does have a bit of theory in the form of the historical roots of statistics and the limitations of statistics that leads to the need for data mining; I found this bit of history quite fascinating and enlightening; it is something I've found in few other data mining books, and I've read several.

The trouble is, I do like theory a bit. I have a master's in computer science, so I'm a bit biased that way, thus my relatively low scoring of the work.

About 1/3rd of the book is dedicated to working through real problems, and that is the overwhelming strength of the book. If you are one who learns by doing rather than by theorizing, you'll find this book outstanding.

The biggest criticism I have of the book is that it is clear that there are significant parts where the authors just didn't have their hearts in it; it felt like they wrote certain sections because the publisher told them they had to in order to hit some type of target marketing segment.

It's also unfortunate that all three software products provided expire in 90 days or less. I'm never one to accomplish anything in 90 days, let alone get through a 700-page technical work!!! I know they are the 3 top mining tools, but I much prefer RapidMiner, a product that is amazingly feature-rich, so easy to use it is actually fun, supported by a robust open-source model, and free.

Overall, a solid work.
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31 of 33 people found the following review helpful By Joseph Hilbe on June 18, 2009
Format: Hardcover
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.
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13 of 15 people found the following review helpful By Anonymous on June 27, 2009
Format: Hardcover Verified Purchase
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.
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10 of 12 people found the following review helpful By Colleen McCue on July 12, 2009
Format: Hardcover
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.
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