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R and Data Mining: Examples and Case Studies Hardcover – Dec 1 2012

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Product Details

  • Hardcover: 256 pages
  • Publisher: Academic Press; 1 edition (Dec 25 2012)
  • Language: English
  • ISBN-10: 0123969638
  • ISBN-13: 978-0123969637
  • Product Dimensions: 15.2 x 1.6 x 22.9 cm
  • Shipping Weight: 590 g
  • Average Customer Review: Be the first to review this item
  • Amazon Bestsellers Rank: #733,297 in Books (See Top 100 in Books)
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Product Description

About the Author

A Senior Data Mining Analyst in Australia Government since 2009.
Before joining public sector, he was an Australian Postdoctoral Fellow (Industry) in the Faculty of Engineering & Information Technology at University of Technology, Sydney, Australia. His research interests include clustering, association rules, time series, outlier detection and data mining applications and he has over forty papers published in journals and conference proceedings. He is a member of the IEEE and a member of the Institute of Analytics Professionals of Australia, and served as program committee member for more than thirty international conferences.

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Most Helpful Customer Reviews on (beta) HASH(0x9afc9a14) out of 5 stars 5 reviews
13 of 13 people found the following review helpful
HASH(0x9b52c4e0) out of 5 stars Low-quality and savagely overpriced March 18 2013
By Dimitri Shvorob - Published on
Format: Hardcover
It's not all bad - I really like the R-resources links in Chapter 15, and give points for Chapters 10 and 11, with basic examples of text mining and network analysis, and for the predictive-modeling case study in Chapter 13. (But why do the percentages on page 172 exceed 100?) However, "R and data mining" is not worth anywhere near $70, and as far as substance and quality are concerned, it is one of the weakest books I have seen. On one hand, you are introduced to several useful built-in R functions and "add-on" R packages, including "party" for classification trees, "cluster" and "fpc" for clustering, "arules" for association-rule learning, "tm" for text mining and "igraph" for network visualization. On the other hand, until Chapter 15, there is pretty little value-added - it's as if the author googled a package, and copy-pasted a vignette from the doc. Things are really basic throughout, even where one might expect complexity - Chapter 14 has the most disappointing example. The page count (200+) overstates content, as the book is seriously heavy on whitespace: code and output, hideously typeset, takes up way more space than needed and is often redundant. I do not recommend the purchase, and suggest "Machine learning with R" by Brett Lantz as a better alternative.

UPD. With the benefit of a little more life experience, I would say: don't spend your time on *any* R book. Python is the way to go.
7 of 7 people found the following review helpful
HASH(0x9b52c534) out of 5 stars Pricey and data unavailable May 1 2013
By chrismatic - Published on
Format: Hardcover
The book is way too pricey for its content and some data in the examples are not even available publicly and need to be purchased separately
5 of 6 people found the following review helpful
HASH(0x9b52c96c) out of 5 stars Not worth buying July 10 2013
By Graham Webster - Published on
Format: Hardcover
I have only read a draft copy that the author has / had on his website, and it is a very disappointing book. For example, the content about each data mining method is very sparse, and as one other reviewer noted, with lots of white space, code, and output. Very little comment about how to use the methods in practice. It certainly looks as though for these chapters the author has copy / pasted material from R package documentation. Not worth buying, there is a lot of other material available of much better quality.
2 of 2 people found the following review helpful
HASH(0x9b52cd2c) out of 5 stars waste of money Aug. 11 2014
By Dirk Dittmer - Published on
Format: Hardcover Verified Purchase
There are better ones. This is a series of screen shots, which are annotated with some text. An O'Reilly book on R is better if you just want a quick reference, so are many online sites. To learn R look for better ones depending on your level of interest and prior knowledge.
0 of 11 people found the following review helpful
HASH(0x9b52ccd8) out of 5 stars A good book. Helped with my datra mining course project July 6 2013
By William M. Ampeh - Published on
Format: Hardcover Verified Purchase
Personally, I think this is a good book. For expect R users, this is provides an overview. For novice, a good reading material on R and data mining. Obviously, no one book with provide you with everything you want, this adding to to your library will help a lot. Good to have and easy to read.