Customer Reviews

Handbook of Statistical Analysis and Data Mining Applications

5 star:		(15)
4 star:		(0)
3 star:		(1)
2 star:		(2)
1 star:		(3)

 

 

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.

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. But to me, theory matters, that's one star down; and rigorous, enthusiastic writing matters, so that's two stars down. In the 3-stars that remain is lots of hands-on practice if you don't mind expiring software, and for that it is very strong.

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.

This is an extraordinary book. So often within this field books are offered as bibles only to fall short. This book does not and delivers a wide array of information and useful tips for the beginner and veteran data miner.

Prior efforts to write a data mining bible have been limited to particular software. Statistical Analysis and Data Mining provides examples from a multitude of data mining software. The examples provided are concise and easy to follow.

Chapter 20, Top 10 Data Mining Mistakes, was one of my favorites. It provided a concise discussion of pitfalls all miners should be aware of and guard against.

Finally, the tutorials (Section III), provide a substantial review of the mining process. The 13 examples cover a wide range of problems and will imbue the reader with a good sense of how data mining works in different scenarios.

Statistical Analysis and Data Mining should be an essential component of every data miner's library.

This is one of the few, of many, data mining books that delivers what it promises. It promises many detailed examples and cases. The companion DVD has detailed cases and also has a real 90 day trial copy of Statistica. I have taught data mining for over 10 years and I know it is very difficult to find comprehensive cases that can be used for classroom examples and for students to actually mine data. The price of the book is also very reasonable expecially when you compare the quantity and quality of the material to the typical intro stat book that usually costs twice as much as this data mining book.
The book also addresses new areas of data mining that are under development. Anyone that really wants to understand what data mining is about will find this book infinetly useful.

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.

discussion proceeds in logical way- start by working one example then go back and get your questions answered. trail software download no problems. highly recommend but must buy hardcopy to get dvd. dvd not included in e download. Amazon very quick to help me cancel e download and order hardcopy once i became aware the content of the dvd not included in e download. complements to author and thanks to Amazon for working problem. With e download text easy read on pc screen not certain would be good read on K.

Nisbet's, Elder's and Miner's book on statistical analysis, was effective in that it:
- gave a intellectual insight into the thinking world of the analyst, as well as
- defined a strong analytics process to follow and
- gave you hands on examples and tool discussions that attempt to implement the intellectual concepts and process.
In the cases of KXEN and SPSS's Clementine. I was able to download their trial software and use this book to exercise the concepts.
I found KXEN's ability to automate the process (and leverage a database engine!) and do much of the analytics at the "click of a button" very powerful, reinforcing much of the book.
It is clear that the "thinking" part of analytics is still important and critical to successful analytics, the automation in KXEN is an effective adjunct and accelerator to the expression of the analyst's intellectual thinking.

As a user of data mining output, it is important that I have a managerial level of the processes, benefits, and pitfalls in data mining. This book is an excellent tool, providing me both high-level information and resources to dig into more details wherever I need. I highly recommend this book for anyone in business who wants to employ data mining as a vital tool to grow their business and improve their bottom line.

I thought from its title that this book not only comes with real world applications but also introduces basic concepts and theory behind these data mining algorithms. I was not asking for in-depth explanation for these algorithms but at least, it has to be able to make us comfortable with these methods. However, after reading these algorithms covered in this book, I still have no idea how these algorithms work and what is the best way to approach different methods. Certainly a big dissapointment for me!