by Joseph Rickert Worldwide R user group activity for the first Quarter of 2014 appears to be way up compared to previous years as the following plot shows. The plot was built by counting the meetings on Revolution Analytics R Community Calendar. R users continue to value the live, in person ... [Read more...]

By Mike Bowles Ensemble methods are the backbone of machine learning techniques. However, it can be a daunting subject for someone approaching it for the first time, so we asked Mike Bowles, machine learning expert and serial entrepreneur to provide some context. Ensemble Methods are among the most powerful and ... [Read more...]

by Joseph Rickert Recently, I had the opportunity to be a member of a job panel for Mathematics, Economics and Statistics students at my alma mater, CSUEB (California State University East Bay). In the context of preparing for a career in data science a student at the event asked: “Where ... [Read more...]

by James Paul Peruvankal, Senior Program Manager at Revolution Analytics At Revolution Analytics, we are always interested in how people teach and learn R, and what makes R so popular, yet ‘quirky’ to learn. To get some insight from a real pro we interviewed Bob Muenchen. Bob is the author ... [Read more...]

by Joseph Rickert I am a book person. I collect books on all sorts of subjects that interest me and consequently I have a fairly extensive collection of R books, many of which I find to be of great value. Nevertheless, when I am asked to recommend an R book ... [Read more...]

by Joseph Rickert In addition to the considerable benefit of being able to meet other, like-minded R users face-to-face, R user groups fill a niche in the world of R education by providing a forum for communicating technical information in an informal and engaging manner. Conferences such as useR!, JSM ... [Read more...]

by Rodney Sparapani, PhD Rodney is an Assistant Professor in the Institute for Health and Society from the Division of Biostatistics at the Medical College of Wisconsin in Milwaukee and president of the Milwaukee Chapter of the ASA which is hosting an R workshop on Data Mining in Milwaukee on ... [Read more...]

by Joseph Rickert After an end-of-year slow down in R user group acrtivity that lasted into mid January, the Revolution Analytics’ Community Calendar indicates that R user groups worldwide are back in full swing with 48 events listed in the short month of February. And, while the total number of active ... [Read more...]

by Daniel Hanson, QA Data Scientist, Revolution Analytics Introduction As most readers are well aware, market return data tends to have heavier tails than that which can be captured by a normal distribution; furthermore, skewness will not be captured either. For this reason, a four parameter distribution such as the ... [Read more...]

by Joseph Rickert One of the key ideas in topological data analysis is to consider a data set to be a sample from a manifold in some high dimensional topological space and then to use the tools of algebraic topology to reconstruct the manifold. It turns out that the converse ... [Read more...]

by James Paul Peruvankal, Senior Program Manager at Revolution Analytics Three weeks ago, researchers at Princeton released a study on Epidemiological modeling of online social network dynamics that states Facebook might lose 80% of its users by 2015-2017. Facebook data scientists hilariously debunked the study stating that Princeton itself would lose ... [Read more...]

by Joseph Rickert Recently, I was trying to remember how to make a 3D scatter plot in R when it occurred to me that the documentation on how to do this is scattered all over the place. Hence, this short organizational note that you may find useful. First of all, ... [Read more...]

by Oliver Vagner, Cloud Solutions Lead Architect at Revolution Analytics Today, I am pleased to announce our new offering in the Amazon Web Services Big Data Marketplace – Revolution R Enterprise 7 for AWS. Of course, if you follow this blog, then you are quite familiar with Revolution R Enterprise (RRE) and ... [Read more...]

by Joseph Rickert The weather is on everybody's mind these days: too much ice and snow east of the Rockies and no rain to speak fo in California. Ram Narasimhan has made it a little easier for R users to keep track of what's going on and also get a ... [Read more...]

by Joseph Rickert Revolution Analytics is announcing three new programs today that we hope will be modest but positive contributions to data science education and public service analytics. The first new program, the Academic Institution Program (AIP) enables colleges, universities and other educational institutions to obtain a site license for ... [Read more...]

by Joseph RIckert Last July, I blogged about rxDTree() the RevoScaleR function for building classification and regression trees on very large data sets. As I explaned then, this function is an implementation of the algorithm introduced by Ben-Haim and Yom-Tov in their 2010 paper that builds trees on histograms of data ... [Read more...]

by Daniel Hanson, QA Data Scientist, Revolution Analytics Introduction and Data Setup Last time, we included a couple of examples of plotting a single xts time series using the plot(.) function (ie, said function included in the xts package). Today, we’ll look at some quick and easy methods for ... [Read more...]

by Joseph Rickert Every once in a while a single book comes to crystallize a new discipline. If books still have this power in the era of electronic media, "Doing Data Science, Straight Talk from the Frontline" by Rachel Schutt and Cathy O’Neil: O'Reilly, 2013 might just be the book ... [Read more...]

by Joseph Rickert When I was in graduate school in the mid '70s Mathematics departments were still under the spell of abstraction for its own sake. At that time, Algebraic Topology which uses concepts from Abstract Algebra to study topological spaces was a major gateway to the realm of ... [Read more...]

by Daniel Hanson QA Data Scientist, Revolution Analytics Some Applications of the xts Time Series Package In our previous discussion, we looked at accessing financial data using the quantmod and Quandl R packages. As noted there, the data series returned by quantmod comes in the form of an xts time ... [Read more...]