Blog Archives

Feuilleton

November 4, 2016
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Feuilleton

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Naive Bayes: A Generative Model and Big Data Classifier

November 2, 2016
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September Package Picks

October 26, 2016
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September Package Picks

by Joseph Rickert September was a bit of a slow month for new R packages. Only 96 new packages showed up un CRAN. Nevertheless, I have picked out 23 for special mention which I have listed in 5 categories. I used the same selection criteria as I described in the post for August picks. Data

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August Package Picks

October 21, 2016
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August Package Picks

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Interview with J.J. Allaire

October 17, 2016
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Interview with J.J. Allaire

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R Packages for Data Access

August 11, 2016
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R Packages for Data Access

by Joseph Rickert Data Science is all about getting access to interesting data, and it is really nice when some kind soul not only points out an interesting data set but also makes it easy for you to access it. Below is a list of 17 R packages that appeared on CRAN between May 1st and August 8th that,...

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Deep Learning Part 1: Comparison of Symbolic Deep Learning Frameworks

August 9, 2016
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by Anusua Trivedi, Microsoft Data Scientist Background and Approach This blog series is based on my upcoming talk on re-usability of Deep Learning Models at the Hadoop+Strata World Conference in Singapore. This blog series will be in several parts – where I describe my experiences and go deep into the reasons behind my choices. Deep learning is an emerging...

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Simulating from the Bivariate Normal Distribution in R

August 4, 2016
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Simulating from the Bivariate Normal Distribution in R

by Joseph Rickert My guess is that a good many statistics students first encounter the bivariate Normal distribution as one or two hastily covered pages in an introductory text book, and then don't think much about it again until someone asks them to generate two random variables with a given correlation structure. Fortunately for R users, a little searching...

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ROC Curves in Two Lines of R Code

August 2, 2016
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ROC Curves in Two Lines of R Code

by Bob Horton, Microsoft Data Scientist ROC curves are commonly used to characterize the sensitivity/specificity tradeoffs for a binary classifier. Most machine learning classifiers produce real-valued scores that correspond with the strength of the prediction that a given case is positive. Turning these real-valued scores into yes or no predictions requires setting a threshold; cases with scores above the...

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An R Users Guide to JSM 2016

July 28, 2016
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by Joseph Rickert My impression is that the JSM has become ever more R friendly over recent years, but with two sessions organized around R tools and several talks featuring R packages, this year may turn out to be the beginning of a new era where conference organizers see value in putting R on the agenda and prospective speakers...

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