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Resampling data in Hadoop with RHadoop

On Revolution Analytics partner Cloudera's blog, Uri Laserson has posted an excellent guide to resampling from a large data set in Hadoop. Resampling is an important step in fitting ensemble models (including random forests and other bagging techniques), and Uri provides a step-by-step guide to implementing resampling methods using RHadoop. He provides the complete map-reduce code in the R language, as well as a useful script for installing RHadoop on a Cloudera instance.   By the way, if you're new to RHadoop, here's RHadoop creator and project leader Antonio Piccolboni introducting RHadoop at last year's Strata CA conference.    Cloudera blog: How-to: Resample from a Large Data Set in Parallel (with R on Hadoop)

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More Stories By David Smith

David Smith is Vice President of Marketing and Community at Revolution Analytics. He has a long history with the R and statistics communities. After graduating with a degree in Statistics from the University of Adelaide, South Australia, he spent four years researching statistical methodology at Lancaster University in the United Kingdom, where he also developed a number of packages for the S-PLUS statistical modeling environment. He continued his association with S-PLUS at Insightful (now TIBCO Spotfire) overseeing the product management of S-PLUS and other statistical and data mining products.<

David smith is the co-author (with Bill Venables) of the popular tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Today, he leads marketing for REvolution R, supports R communities worldwide, and is responsible for the Revolutions blog. Prior to joining Revolution Analytics, he served as vice president of product management at Zynchros, Inc. Follow him on twitter at @RevoDavid