Blog Archives

R / Finance 2014: Packaged Takeaways

May 29, 2014
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R / Finance 2014: Packaged Takeaways

by Joseph Rickert I was very happy to have been able to attend R / Finance 2014 which wrapped up a couple of weeks ago. In general, the talks were at a very high level of play, some dealing with brand new ideas and many presented at a significant level of technical or mathematical sophistication. Fortunately, most of the...

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Quick History 2: GLMs, R and large data sets

May 22, 2014
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by Joseph Rickert In last week’s post, I sketched out the history of Generalized Linear Models and their implementations. In this post I’ll attempt to outline how GLM functions evolved in R to handle large data sets. The first function to make it possible to build GLM models with datasets that are too big to fit into memory was...

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Ensemble Methods Part 3: Revolution Analytics Big Data Random Forest Function

May 20, 2014
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Ensemble Methods Part 3: Revolution Analytics Big Data Random Forest Function

by Mike Bowles In two previous posts, A Thumbnail History of Ensemble Methods and Ensemble Packages in R, Mike Bowles — a machine learning expert and serial entrepreneur — laid out a brief history of ensemble methods and described a few of the many implementations in R. In this post Mike takes a detailed look at the Random Forests...

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Quick History: glm()

May 15, 2014
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by Joseph Rickert I recently wrote about some R resources that are available for generalized linear models (GLMs). Looking over the material, I was amazed by the amount of effort that is continuing to go into GLMs, both with with respect to new theoretical developments and also in response to practical problems such as the need to deal with...

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Plotly and rOpenSci: Make ggplots shareable and interactive.

May 13, 2014
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Plotly and rOpenSci: Make ggplots shareable and interactive.

By Matt Sundquist Plotly's Co-Founder Here at Plotly, we are on a mission to build a platform where data scientists can analyze data, create beautiful graphs and collaborate: like a GitHub for data, where you can share and find plots, data, and code. The benefits are: Plots (including ggplot2 plots) are interactive and drawn with D3 (try zooming, panning,...

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R and Finance

May 8, 2014
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by Joseph Rickert R/Finance 2014 is just about a week away. Over the past four or five years this has become my favorite conference. It is small (300 people this year), exceptionally well-run, and always offers an eclectic mix of theoretical mathematics, efficient, practical computing, industry best practices and trading “street smarts”. This clip of Blair Hull delivering a...

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R and the Collatz Conjecture: Part 2

May 6, 2014
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by Seth Mottaghinejad, Analytic Consultant for Revolution Analytics In the last article, we showed two separate R implementations of the Collatz conjecture: 'nonvec_collatz' and 'vec_collatz', with the latter being more efficient than the former because of the way it takes advantage of vectorization in R. Let's once again take a look at 'vec_collatz': vec_collatz .01) { + niter...

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Importing a log file with rxImport()

May 1, 2014
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by Joseph Rickert Tuesday's post on a new Kaggle contest mentioned that Revolution Analytics offers a free trial for using Revolution R Enterprise in the Amazon cloud. One reason this might be of interest to contestants is the rxImport() function which reads delimited text data, fixed format text data, and with an appropriate ODBC driver, data stored in a...

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Predict which shoppers will become repeat buyers

April 29, 2014
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Predict which shoppers will become repeat buyers

by James P. Peruvankal Kaggle just announced a competition to predict which shoppers will become repeat buyers. To aid with algorithmic development, they have provided complete, basket-level, pre-offer shopping history for a large set of shoppers who were targeted for an acquisition campaign. Files containing the incentives offered to each shopper as well as their post-incentive behavior are also...

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R Helps With Employee Churn

April 24, 2014
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R Helps With Employee Churn

by Joseph Rickert Pasha Roberts, Chief Scientist at Talent Analytics, is writing a series of articles on Employee Churn for the Predictive Analytics Times that comprise a really instructive and valuable example of using R to do some basic predictive modeling. So far, Pasha has published Employee Churn 201 in which he makes a case for the importance of...

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