Book title: Data Mining Applications with R
Editors: Yanchang Zhao, Yonghua Cen
Publisher: Elsevier
Publish date: December 2013
ISBN: 978-0-12-411511-8
Length: 514 pages
URL: http://www.rdatamining.com/books/dmar
An edited book titled Data Mining Applications with R was released in December 2013, which features 15 real-word applications on data mining with R.
R code, data and color figures for the book
Buy the book on
– Amazon
– Elsevier
– Google Books
Below is its table of contents.
- Foreword
Graham Williams - Chapter 1 Power Grid Data Analysis with R and Hadoop
Terence Critchlow, Ryan Hafen, Tara Gibson and Kerstin Kleese van Dam - Chapter 2 Picturing Bayesian Classifiers: A Visual Data Mining Approach to Parameters Optimization
Giorgio Maria Di Nunzio and Alessandro Sordoni - Chapter 3 Discovery of emergent issues and controversies in Anthropology using text mining, topic modeling and social network analysis of microblog content
Ben Marwick - Chapter 4 Text Mining and Network Analysis of Digital Libraries in R
Eric Nguyen - Chapter 5 Recommendation systems in R
Saurabh Bhatnagar - Chapter 6 Response Modeling in Direct Marketing: A Data Mining Based Approach for Target Selection
Sadaf Hossein Javaheri, Mohammad Mehdi Sepehri and Babak Teimourpour - Chapter 7 Caravan Insurance Policy Customer Profile Modeling with R Mining
Mukesh Patel and Mudit Gupta - Chapter 8 Selecting Best Features for Predicting Bank Loan Default
Zahra Yazdani, Mohammad Mehdi Sepehri and Babak Teimourpour - Chapter 9 A Choquet Ingtegral Toolbox and its Application in Customer’s Preference Analysis
Huy Quan Vu, Gleb Beliakov and Gang Li - Chapter 10 A Real-Time Property Value Index based on Web Data
Fernando Tusell, Maria Blanca Palacios, María Jesús Bárcena and Patricia Menéndez - Chapter 11 Predicting Seabed Hardness Using Random Forest in R
Jin Li, Justy Siwabessy, Zhi Huang, Maggie Tran and Andrew Heap - Chapter 12 Supervised classification of images, applied to plankton samples using R and zooimage
Kevin Denis and Philippe Grosjean - Chapter 13 Crime analyses using R
Madhav Kumar, Anindya Sengupta and Shreyes Upadhyay - Chapter 14 Football Mining with R
Maurizio Carpita, Marco Sandri, Anna Simonetto and Paola Zuccolotto - Chapter 15 Analyzing Internet DNS(SEC) Traffic with R for Resolving Platform Optimization
Emmanuel Herbert, Daniel Migault, Stephane Senecal, Stanislas Francfort and Maryline Laurent
Advertisements
Hello Yanchang ,
I suspect this post would greatly benefit from adding some pictures to it.
If you will do so – e-mail me so I could update the post on r-bloggers.
Good luck with your new book, it looks very interesting 🙂
With regards,
Tal
Thank you for your suggestion. I have added some pictures to the blog post. Could you please update the corresponding page on r-bloggers?
Thanks and have a happy holiday.
Reblogged this on Drug and other Products Counterfeits Mining.
Hi,
I am new in data mining. and Hoped that I can learn advanced data mining via step-by-step fashion by following the book samples. The samples presented in the book are all good examples. But many R code don’t run. and some dataset mentioned in R cannot be found or in different format. some Amonzon readers hope you can provide R and data set updates. Is it possible to provide a more consistent supplimental material via RDataMining.com?
Thank you,
My apologies for inconsistency in code/data formatting and possible errors in them, and thanks for your suggestion. I am working on that and hopefully will provide updated versions of code/data soon after contacting chapter authors.
Thank you for your reply.
I just updated my review on amazon and gave it 4 stars. I like the book’s style – learning by doing