In case you missed them, here are some articles from May of particular interest to R users. R tops the annual KDNuggets Data Mining Software poll for the first time. R 2.15.1 is scheduled for June 22. (Revolution R Enterprise 6, released on June 5, is based on 2.14.2.) A tutorial uses R, Hadoop, and the RHadoop project to...
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Data distillation with Hadoop and R
We're definitely in the age of Big Data: today, there are many more sources of data readily available to us to analyze than there were even a couple of years ago. But what about extracting useful information from novel data streams that are often noisy and minutely transactional ... aye, there's the rub. One of the great things about...
Book Review: Parallel R
You have a problem: R is single-threaded, but your code would be faster if it could simultaneously run on more than one core. You have access to a cluster and/or your computer has multiple cores. Parallel R, by Q. Ethan McCallum and Stephen...
Facebook-class social network analysis with R and Hadoop
In computing, social networks are traditionally represented as graphs: a connection of nodes (people), pairs of which may be connected by edges (friend relationships). Visually, the social networks can then be represented like this: Social network analysis often amounts to calculating the statistics on a graph like this: the number of edges (friends) connected to a particular node (person),...
Orbitz: R has become the data-mining tool of choice
Sameer Chopra, vice president of Advanced Analytics at Orbitz Worldwide, wrote recently in Analytics magazine about the changing landscape of processes, software and systems for statistical modelers. In a section on "Big Data and Open Source Analytics", Chopra lays out the reasons why the R language "has become the data-mining tool of choice for machine learners": R has very...
Revolution Newsletter: May 2012
The most recent edition of the Revolution Newsletter is out. The news section is below, and you can read the full May edition (with highlights from this blog and community events) online. You can subscribe to the Revolution Newsletter to get it monthly via email. New R Training Courses Announced. Three new R courses from leading R experts are...
In case you missed it: April 2012 Roundup
In case you missed them, here are some articles from April of particular interest to R users. Information Age published a feature article on R, describing how new graduates are driving adoption of R in industry. Bob Muenchen has updated his list of R package equivalents to SAS and SPSS procedures. A history of Data Science, including Bill Cleveland's...
Heartbeat of a Cycling City: Bixi data at Hack/Reduce
The recent Hack/Reduce hackathon in Montreal was a tonne of fun. Our team tackled a data set of consisting of Bixi (Montreal’s bicycle share system) station states at one minute temporal resolution. We used Hadoop and mapreduce to pull out some features of user behaviours. One of the things we extracted was the flux at 
Online resources for handling big data and parallel computing in R
by Yanchang Zhao, RDataMining.com Compared with many other programming languages, such as C/C++ and Java, R is less efficient and consumes much more memory. Fortunately, there are some packages that enables parallel computing in R and also packages for processing … Continue reading →
Big Data Analytics with R and Hadoop
The open-source RHadoop project makes it easier to extract data from Hadoop for analysis with R, and to run R within the nodes of the Hadoop cluster -- essentially, to transform Hadoop into a massively-parallel statistical computing cluster based on R. In yesterday's webinar (the replay of which is embedded below), Data scientist and RHadoop project lead Antonio Piccolboni...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
