>From an email list:
"R is well known in the world of Big Data and is increasing in popularity. A
number of very useful resources are available for anyone undertaking data
mining in R.
For example, Luis Torgo has just published a book called Data Mining with R �
learning with case studies (Torgo, Luis. Data Mining with R. ), and presents a
set of four case studies with accompanying data sets and code which the
interested student can work through. Torgo�s book provides the usual analytic
and graphical techniques used every day by data miners, including specialized
visualization techniques, dealing with missing values, developing prediction
models, and methods for evaluating the performance of your models.
Also of interest to the data miner is the Rattle (R Analytical Tool to Learn
Easily) GUI. Rattle is a data mining facility for analyzing very large data
sets. It provides many useful statistical and graphical data summaries,
presents mechanisms for developing a variety of models, and summarizes the
performance of your models.
Another web-site worth reading is the following:
http://www.revolutionanalytics.com/";
Also check this book (free and recommended by John Hopskins' Department of
Statistics".
Best regards,
Angel Rodriguez-Laso
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