Publications by Joseph Rickert
More R User Group Sites
by Joseph Rickert Last month I wrote about how several R user groups were making use of GitHub and listed some sites that I thought had interesting material. A few readers were kind enough to point out sites that I had missed; so I would just like to give a couple of “shout outs” here. First of all, I should acknowledge LondonR as a leader in...
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Bay Area useR Group Lightning Talks
by Joseph Rickert Earlier this month the Bay Area useR Group (BARUG) held it annual lightning talk meeting. This is by far our most popular meeting format: eight, 15 minute talks (12 minutes speaking and 3 minutes Q & A while the next speaker is setting up) packed into a two hour time slot. The intensity seems to really energize the speakers and ...
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Analysis of Xbox Usage Trends with R: Time Series Decompositions
by Daniel MooreDirector of Applied Statistics Engineering, Console DevelopmentMicrosoft In Xbox Hardware, we are interested in the various ways that our hardware is used, and we are especially interested in how that usage changes over time. We employ several several time series analysis techniques that are helpful in getting a holistic view of us...
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Generating and Visualizing Multivariate Data with R
By Joseph Rickert The ability to generate synthetic data with a specified correlation structure is essential to modeling work. As you might expect, R’s toolbox of packages and functions for generating and visualizing data from multivariate distributions is impressive. The basic function for generating multivariate normal data is mvrnorm() from ...
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Analysing the movements of a cat
by Verena Haunschmid Since I have a cat tracker, I wanted to do some analysis of the behavior of my cats. I have shown how to do some of these things here. Data Collection The data was collected using the Tractive GPS Pet Tracker over a period of about one year from January 2014 to November 2014 (with breaks). From March to November I addition...
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Confidence Intervals for Random Forests
by Joseph Rickert Random Forests, the “go to” classifier for many data scientists, is a fairly complex algorithm with many moving parts that introduces randomness at different levels. Understanding exactly how the algorithm operates requires some work, and assessing how good a Random Forests model fits the data is a serious challenge. In the...
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Bay Area R User Group at Strata and PAW
by Joseph Rickert I always think of Strata Hadoop World and Predictive Analytics World as initiating the Spring conference season here in the San Francisco Bay Area. The rainy season is usually over by the end of March and it is a perfect time to visit. If you are traveling to either of these conferences from out of town and you are an R aficiona...
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Computing Classification Evaluation Metrics in R
by Said Bleik, Shaheen Gauher, Data Scientists at Microsoft Evaluation metrics are the key to understanding how your classification model performs when applied to a test dataset. In what follows, we present a tutorial on how to compute common metrics that are often used in evaluation, in addition to metrics generated from random classifiers, whi...
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Scoring R Models with Excel
by Joseph Rickert In a post late last year, my colleague and fellow blogger, Andrie de Vries described enhancements to the AzureML R package that makes it easy to publish R functions that consume data frames as Azure Web Services. A very nice consequence is that it is now feasible to develop predictive models in R and enable the Excel powered bus...
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Get ready for the New York R Conference
by Joseph Rickert Last year, I wrote the New York R Conference “set the bar pretty darn high for a first time conference”. Not only was there an outstanding lineup of speakers, but the energy and enthusiasm that conference attendees brought with them, or maybe just generated on the spot, was remarkable. This year I am definitely looking forw...
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