predictive analytics

Orbitz and the Macs: Signals, not segmentation

June 27, 2012 | David Smith

By now you've probably heard about the fact that Orbitz users accessing the site via Macs are seeing more expensive hotel options when they search. But it seems worth clearing up a couple of fallacies. First, it's not as if the same hotel room is being offered at a higher ... [Read more...]

R Tops Data Mining Software Poll

May 31, 2012 | David Smith

For the past 12 years, KDNuggets has conducted an annual poll asking "What analytics/data mining software you used in the past 12 months for a real project (not just evaluation)". In this year's poll, R was the top-ranked data mining solution, selected by 30.7% of poll respondents. Microsoft Excel was second, at 29.8%. ... [Read more...]

R is to SAS as Java is to COBOL

May 18, 2012 | David Smith

An interview with Revolution Analytics CEO Dave Rich was published this week by BeyeNetwork. During the interview, Dace was asked about how the statistical modeling platforms have changed over the decades: People have been doing statistical modeling and predictive analytics for 50 years now, SAS and SPSS have been around since ... [Read more...]

Simple tools for building a recommendation engine

April 19, 2012 | Joseph Rickert

By Joseph Rickert Revolution’s resident economist, Saar Golde, is very fond of saying that “90% of what you might from a recommendation engine can be achieved with simple techniques”. To illustrate this point (without doing a lot of work), we downloaded the million row movie dataset from www.grouplens.org ... [Read more...]

Marketing optimization with LityxIQ

April 3, 2012 | David Smith

Marketing is one of the pioneering domains when it comes to applications of predictive analytics to Big Data. (For example, how Target used statistical modeling to predict demographic attribues of customers, like pregnancy, to target coupons.) To get such powerful insights into the hands of marketers, DC-area company LityxIQ provides ... [Read more...]

Predicting Marketing Campaign with R

March 17, 2012 | Arun Gaikwad

In my last blog I created a mechanism to fetch data from Salesforce using rJava and SOQL. In this blog I am going to use that mechanism to fetch ad campaign data from salesforce and predict future ad campaign sales using R Let us assume that Salesforce has campaign data ... [Read more...]

Big-data Naive Bayes and Classification Trees with R and Netezza

March 8, 2012 | David Smith

The IBM Netezza analytics appliances combine high-capacity storage for Big Data with a massively-parallel processing platform for high-performance computing. With the addition of Revolution R Enterprise for IBM Netezza, you can use the power of the R language to build predictive models on Big Data. In the demonstration below, Revolution ... [Read more...]

Big Data Analytics to Revolutionize Services

March 6, 2012 | David Smith

Revolution Analytics' CEO Dave Rich was interviewed by Wikibon's David Vellante and SiliconAngle's John Furrier at the Strata 2012 conference last week. Given Dave's background at Accenture Analytics, the conversation naturally turned to impact of predictive analytics and R on business services. (See the video after the jump, below.) Bret Latmore ... [Read more...]

ACM Data Mining Camp 2011: Report

October 18, 2011 | Joseph Rickert

(By Joseph Rickert.) In San Jose topics like big data, map reduce, predictive models, mobile analytics and crowdsourcing draw a crowd even on a Saturday. So it turned out that the ACM data Mining Camp and "un-conference" was a very "happening" way to spend a Saturday. Over 500 people attended the ... [Read more...]

Big Analytics: Closing the "clue gap" with Big Data

August 31, 2011 | David Smith

There's been an growing discussion over the past couple of years on the topic of Big Data: how to deal with the situation when you have more data than can be conveniently managed and analyzed by traditional software tools. But Big Data has little intrinsic value in its own right: ... [Read more...]

How Google uses R to make online advertising more effective

August 3, 2011 | David Smith

At JSM 2011 today, three Google employees (amongst the more than 20 Google delegates there) gave a little insight into how statistical analysis with R yields better results for companies using Google's various advertising products. Bill Heavlin from Google kicked off the session with a talk about conditional regression models, a statistical ... [Read more...]

Sentiment Analysis for Airlines via Twitter

July 5, 2011 | David Smith

Last weekend here in the states was the 4th of July long weekend, one of the busier air travel days of the year. As anyone who flies in the States knows, with air travel often comes frustration, and in this social media age many express their frustration on Twitter: The ... [Read more...]

K-Means Clustering on Big Data

June 7, 2011 | Joseph Rickert

In this post Joseph Rickert demonstrates how to build a classification model on a large data set with the RevoScaleR package. A script file for use with Revolution R Enterprise to recreate the analysis below is at the end of the post, and can also be downloaded here -- ed. ... [Read more...]

Participate in the 2011 Rexer Data Mining Survey

May 23, 2011 | David Smith

Last year's Rexer Data Mining Survey reported that R is used by more data miners than any other tool. If you're using R for data mining or data analysis generally, be counted at the 2011 Data Miner Survey (use access code: RL3X2), which closes in early June. Here's some background ... [Read more...]

Quantifying gravitational lensing by dark matter

May 23, 2011 | David Smith

The latest prediction competition at Kaggle is literally "out of this world": the goal is to quantify the shape of 2-D images of galaxies from a simulated telescope, to test models for how invisible dark matter in the Universe distorts the images through gravitational lensing (as shown in the image ... [Read more...]

How Kaggle competitors use R

April 19, 2011 | David Smith

The competitive data prediction competitions hosted by Kaggle require data scientists to bring their A game: the competition is intense, and competitors know in real time from the daily leaderboards how their predictions compare in accuracy to those of their rivals. So it's no surprise that open-source R, the most ... [Read more...]
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