by Herman Jopia What is Binning? Binning is the term used in scoring modeling for what is also known in Machine Learning as Discretization, the process of transforming a continuous characteristic into a finite number of intervals (the bins), which allows for a better understanding of its distribution and its ... [Read more...]

by Joseph Rickert The gradient boosting machine as developed by Friedman, Hastie, Tibshirani and others, has become an extremely successful algorithm for dealing with both classification and regression problems and is now an essential feature of any machine learning toolbox. R’s gbm() function (gbm package) is a particularly well ... [Read more...]

by Gary R. Moser Director of Institutional Research and Planning The California Maritime Academy I recently contacted Joseph Rickert about inviting Vim guru Drew Niel (web: vimcasts.org, book: "Practical Vim: Edit Text at the Speed of Thought") to speak at the Bay Area R User Group group. Due to ... [Read more...]

by Joseph Rickert What will you be doing at 26 minutes and 53 seconds past 9 this coming Saturday morning? I will probably be running simulations. I have become obsessed with an astounding result from number theory and have been trying to devise Monte Carlo simulations to get at it. The result, well ... [Read more...]

by Joseph Rickert R user group activity is still on the rise. The following plot of the number of R user group meetings listed on Revolution Analytics' Community Calendar over the most recent 114 weeks shows a slight to upward trend along with a couple of annual cycles. Predictably, meetings trail ... [Read more...]

by Matt Sundquist co-founder of Plotly Domino's new R Notebook and Plotly's R API let you code, make interactive R and ggplot2 graphs, and collaborate entirely online. Here is the Notebook in action: Published R Notebook To execute this Notebook, or to build your own, head to Domino's Plotly Project. ... [Read more...]

by Joseph Rickert Distcomp, a new R package available on GitHub from a group of Stanford researchers has the potential to significantly advance the practice of collaborative computing with large data sets distributed over separate sites that may be unwilling to explicitly share data. The fundamental idea is to be ... [Read more...]

by Joseph Rickert For the past few years, the Strata + Hadoop World Conference in San Jose has kicked off my personal conference season. With its focus on Data Science, Strata always seems to present some interesting R related talks, and I am looking forward to the various events over the ... [Read more...]

by Joseph Rickert In the last week of January, HP Labs in Palo Alto hosted a workshop on distributed computing in R that was organized by Indrajit Roy (Principal Researcher, HP) and Michael Lawrence (Genentech and R-core member). The goal was to bring together a small group of R developers ... [Read more...]

James Peruvankal Sr. Program Manager, Revolution Analytics Information about the technology business ecosystems is valuable to both established companies as well as startups. Fortunately CrunchBase - the world’s most comprehensive dataset of startup activity, captures quite a bit of such information. Founded in 2007 by Mike Arrington, CrunchBase began as ... [Read more...]

by Joseph Rickert Learning to effectively use any of the dozens of popular machine learning algorithms requires mastering many details and dealing with all kinds of practical issues. With all of this to consider, it might not be apparent to a person coming to machine learning from a background other ... [Read more...]

by Siddarth Ramesh R Programmer, Revolution Analytics A couple of months ago, I worked on a customer engagement involving Shiny. Shiny is a package created by RStudio that is intended to make plots dynamic and interactive. One advantage of Shiny is that an app would completely be written in R, ... [Read more...]

by Joseph Rickert With a membership that spans the entire Bay Area and the ability to hold meetings from San Jose to San Francisco, the Bay Area useR Group is in the very fortunate position of being able to attract world-class R speakers on a regular basis. Meetings that feature ... [Read more...]

by Norman Matloff You've heard that graphics processing units — GPUs — can bring big increases in computational speed. While GPUs cannot speed up work in every application, the fact is that in many cases it can indeed provide very rapid computation. In this tutorial, we'll see how this is done, both ... [Read more...]

by Joseph Rickert Apache Spark, the open-source, cluster computing framework originally developed in the AMPLab at UC Berkeley and now championed by Databricks is rapidly moving from the bleeding edge of data science to the mainstream. Interest in Spark, demand for training and overall hype is on a trajectory to ... [Read more...]

by Bob Horton, Data Scientist, Revolution Analytics From electronic medical records to genomic sequences, the data deluge is affecting all aspects of health care. The Masters of Science in Health Informatics (MSHI) program at the University of San Francisco, now in its second year, is designed to help students develop ... [Read more...]

by Joseph Rickert One of the greatest strengths of the R language is surely the base graphics capabilities. Grid graphics, lattice, ggplot2, bigvis and the many R packages that interface with javascript D3 graphics have added astounding capabilities, well beyond what can be achieved with base graphics alone. Nevertheless, the ... [Read more...]

by Nick Elprin Co-Founder Domino Data Lab "R Notebooks" use the IPython Notebook UI to run R (rather than Python) in notebook cells, giving you an interactive R environment hosted on scalable servers, accessible through a web browser. This post describes how and why we built our "R Notebooks" feature. ... [Read more...]

by Joseph Rickert KatRisk, a Berkeley based catastrophe modeling company specializing in wind and flood risk, has put three R and Shiny powered interactive demos on their website. Together these provide a nice introduction to the practical aspects of weather based risk modeling and give a good indication of the ... [Read more...]

Cusby Ryan Garner Senior Data Scientist, Revolution Analytics I love creating spatial data visualizations in R. With the ggmap package, I can easily download satellite imagery which serves as a base layer for the data I want to represent. In the code below, I show you how to visualize sampled ... [Read more...]