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<rss version="2.0" xmlns:wfw="http://wellformedweb.org/CommentAPI/"><channel><title>mloss.org pGBRT, Parallel Gradient Boosted Regression Trees</title><link>http://mloss.org</link><description>Updates and additions to pGBRT, Parallel Gradient Boosted Regression Trees</description><language>en</language><lastBuildDate>Fri, 16 Sep 2011 22:15:46 -0000</lastBuildDate><item><title>pGBRT, Parallel Gradient Boosted Regression Trees 0.9</title><link>http://mloss.org/software/view/332/</link><description>&lt;html&gt;&lt;p&gt;The package pGBRT implements a parallel algorithm for training gradient boosted regression trees (GBRT). The software learns an ensemble of truncated regression trees on a feature-wise distributed training set. Written in C++ with parallel/distributed communication provided by MPI, pGBRT supports efficient execution on both shared memory and cluster systems.
&lt;/p&gt;&lt;/html&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">Stephen Tyree, Killian Q. Weinberger, Kunal Agrawal</dc:creator><pubDate>Fri, 16 Sep 2011 22:15:46 -0000</pubDate><comments>http://mloss.org/software/rss/comments/332</comments><guid>http://mloss.org/software/view/332/</guid><category>distributed</category><category>parallel</category><category>gradient boosting</category></item></channel></rss>