Blog Archives

The R Consortium Gears Up For Business

September 24, 2015
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The R Consortium Gears Up For Business

by Joseph Rickert This week, the Infrastructure Steering Committee (ISC) of the R Consortium unanimously elected Hadley Wickham as its chair thereby also giving Hadley a seat on the R Consortium board of directors. Congratulations Hadley!! This is a major step forward towards putting the R Consortium in business. Not only is the ISC the group that will decide...

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How do you know if your model is going to work? Part 4: Cross-validation techniques

September 22, 2015
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How do you know if your model is going to work? Part 4: Cross-validation techniques

by John Mount (more articles) and Nina Zumel (more articles). In this article we conclude our four part series on basic model testing. When fitting and selecting models in a data science project, how do you know that your final model is good? And how sure are you that it's better than the models that you rejected? In this...

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Reading Financial Time Series Data with R

September 17, 2015
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Reading Financial Time Series Data with R

by Joseph Rickert In a recent post focused on plotting time series with the new dygraphs package, I did not show how easy it is to read financial data into R. However, in a thoughtful comment to the post, Achim Zeileis pointed out a number of features built into the basic R time series packages that everyone ought to...

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The New Microsoft Data Science User Group Program

September 10, 2015
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by Joseph Rickert We are very pleased to announce that Microsoft will not only continue the Revolution Analytics’ tradition of supporting R user groups worldwide, but is expanding the scope of the user group program. The new 2016 Microsoft Data Science User Group Sponsorship Program is open to all user groups that are passionate about open-source data science technologies....

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How do you know if your model is going to work? Part 2: In-training set measures

September 8, 2015
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How do you know if your model is going to work? Part 2: In-training set measures

by John Mount (more articles) and Nina Zumel (more articles) When fitting and selecting models in a data science project, how do you know that your final model is good? And how sure are you that it's better than the models that you rejected? In this Part 2 of our four part mini-series "How do you know if your...

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How do you know if your model is going to work? Part 1: The Problem

September 3, 2015
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How do you know if your model is going to work? Part 1: The Problem

by John Mount (more articles) and Nina Zumel (more articles) of Win-Vector LLC "Essentially, all models are wrong, but some are useful." George Box Here's a caricature of a data science project: your company or client needs information (usually to make a decision). Your job is to build a model to predict that information. You fit a model, perhaps...

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Looking after Datasets

September 1, 2015
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Looking after Datasets

by Antony Unwin University of Augsburg, Germany David Moore's definition of data: numbers that have been given a context. Here is some context for the finch dataset: Fig 1: Illustrations of the beaks of four of Darwin's finches from "The Voyage of the Beagle". Note that only one of these (fortis) is included in the dataset. R's package system...

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Plotting Time Series in R using Yahoo Finance data

August 27, 2015
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Plotting Time Series in R using Yahoo Finance data

by Joseph Rickert I recently rediscovered the Timely Portfolio post on R Financial Time Series Plotting. If you are not familiar with this gem, it is well-worth the time to stop and have a look at it now. Not only does it contain some useful examples of time series plots mixing different combinations of time series packages (ts, zoo,...

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Following up on news stories with choroplethr and R

August 25, 2015
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Following up on news stories with choroplethr and R

by Ari Lamstein, consultant specializing in software engineering and data analysis and author of the free email course Learn to Map Census Data in R. One of my favorite things about R is that it allows me to follow up on interesting news stories. Consider this interview on EconTalk about the history of fracking in America. Russ Roberts interviewed...

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5 New R Packages for Data Scientists

August 20, 2015
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5 New R Packages for Data Scientists

by Joseph Rickert One great beauty of the R ecosystem, and perhaps the primary reason for R’s phenomenal growth, is the system for contributing new packages. This, coupled to the rock solid stability of CRAN, R’s primary package repository, gives R a great advantage. However, anyone with enough technical knowhow to formulate a proper submission can contribute a package...

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