Data Mining Using SAS Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) [Hardcover]

George Fernandez (Author)

Book Description

Publication Date: December 27, 2002 | ISBN-10: 1584883456 | ISBN-13: 978-1584883456 | Edition: 1

Most books on data mining focus on principles and furnish few instructions on how to carry out a data mining project. Data Mining Using SAS Applications not only introduces the key concepts but also enables readers to understand and successfully apply data mining methods using powerful yet user-friendly SAS macro-call files. These methods stress the use of visualization to thoroughly study the structure of data and check the validity of statistical models fitted to data.

Learn how to convert PC databases to SAS data

Discover sampling techniques to create training and validation samples

Understand frequency data analysis for categorical data

Explore supervised and unsupervised learning

Master exploratory graphical techniques

Acquire model validation techniques in regression and classification

The text furnishes 13 easy-to-use SAS data mining macros designed to work with the standard SAS modules. No additional modules or previous experience in SAS programming is required. The author shows how to perform complete predictive modeling, including data exploration, model fitting, assumption checks, validation, and scoring new data, on SAS datasets in less than ten minutes!

Product Details

• Hardcover: 367 pages
• Publisher: Chapman and Hall/CRC; 1 edition (December 27, 2002)
• Language: English
• ISBN-10: 1584883456
• ISBN-13: 978-1584883456
• Product Dimensions: 9.2 x 6.4 x 1 inches
• Shipping Weight: 1.5 pounds
• Average Customer Review: 4.0 out of 5 stars  See all reviews (6 customer reviews)
• Amazon Best Sellers Rank: #1,452,175 in Books (See Top 100 in Books)

More About the Author

George Fernandez is a professor of applied statistical methods and serves as the director for the University of Nevada - Reno Center for Research Design and Analysis. His publication records include, applied statistics book, a CD-Rom, 60 journal papers, and more than 30 conference proceedings. Dr. Fernandez has more than 23 years of experience in teaching applied statistics courses and SAS programming.
He won several best paper and poster presentation awards at the regional and international conferences. He has presented several invited full-day workshops on "Applications of user-friendly statistical methods in Data mining:
American Statistical Association Joint meeting in Atlanta (2001), Western SAS users conference in Arizona (2000), in San Diego (2002), and San Jose (2005), 56th Deming's conference, Atlantic City (2003), Key-note Speaker and workshop presenter, 16th Conference on Applied Statistics, Kansas State University and full-day workshop presenter at the 57th session of International Statistical Institute conference at Durbin South Africa (2009). His recent discovery, 'A new and simpler way to calculate body's Maximum Weight Limit-BMI made simple' and his new books on "User-friendly childhood obesity screening tools" received worldwide recognition.

Customer Reviews

Most Helpful Customer Reviews

20 of 20 people found the following review helpful:

4.0 out of 5 stars This is a good book for SAS applications, but..., October 5, 2003

By 

Megan Squire (Gibsonville, NC USA) - See all my reviews
(REAL NAME)   

This review is from: Data Mining Using SAS Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) (Hardcover)

Overall, this book is quite good. I wish I had it when I was working on my dissertation. I used all of the techniques in this book with SAS, and had to figure out this stuff on my own. I wish I hadn't had to go through all that, although it was a good learning experience. If I had had a resource like this book then I could have devoted more time to exploratory analysis and less time to the nuts and bolts of getting the programs to run.

I only gave it 4 stars however, because I thought the last chapter should be removed entirely. Reading Chapter 7 made me doubt the author throughout the whole rest of the book, which is not a good sign. Problems, some minor: neural networks are hardly an "emerging technology" for data mining. "Data warehousing" is not really a data mining technology, at least not how "technology" is defined throughout the whole rest of the book (i.e. as a technique). First and foremost, data warehousing is an organizational method for data, not a technique for analyzing it (which is what every single other topic covered in this book is designed to do: analyze). Market basket analysis is just ONE WAY to describe association rule mining. All association rules are NOT designed to help with marketing. This author obviously read Barry & Linoff (Data Mining for Marketing, Sales, and Customer Support) for his definition of what association rules are good for, and missed the whole point of how they can be used with ANY data, not just marketing data. Lastly, his bibliography in Chapter 7 is very thin; if his treatment of these "emerging technologies" is going to be so cursory, at least give the reader some decent pointers to more appropriate texts.

Another picky point: the beginning of the book talks about how it is designed to show how to use SAS if you DON'T have Enterprise Miner (which is good, since that's a really expensive thing that most students and faculty can't afford). And then this last chapter begins by saying how it will cover three emerging technologies for which you can use SAS ... which is all well and good, until you get to the last sentence of the last chapter, which says that you must use Enterprise Miner to do anything with these three emerging technologies. How frustrating for the reader who thinks they're going to cover emerging technologies the same way as the whole rest of the book!

Anyway, just ignore the last chapter of this book and enjoy the first 6. This book will definitely save you some time if you are interested in prediction, classification, clustering, principal components analysis, or common factor analysis.

5 of 6 people found the following review helpful:

5.0 out of 5 stars Cool SAS macros for data mining, May 2, 2003

By A Customer

This review is from: Data Mining Using SAS Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) (Hardcover)

Very cool time saving SAS macros are included in this book. I used these macros daily to generate SAS graphs, analysis, html outputs etc in SAS Learning edition. The author updates the macros frequantly and I found out about the SAS learning edition recently by visiting the books web page ...

It is a unique approch to use SAS.

2 of 2 people found the following review helpful:

2.0 out of 5 stars Not Algorithmic Data Mining, April 18, 2006

By 

J. Roy (San Antonio, TX) - See all my reviews
(REAL NAME)   

This review is from: Data Mining Using SAS Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) (Hardcover)

SAS is not the best system for data mining to begin with. R (or S-plus) seems to provide a much stronger framework and packages for Classification and Regression Trees, Random Forests, Neural Networks etc. SAS cannot really do any of these with the base system.

All of the techniques covered in this book are fairly standard statistical techniques that don't really match with what I consider data mining to be (i.e. regression, principal component analysis, discrimination analysis). There are better texts for these techniques that cover both the theory and code more indepth.