This document discusses modeling algorithms using the MapReduce framework. It outlines types of learning that can be done in MapReduce, including parallel training of models, ensemble methods, and distributed algorithms that fit the statistical query model (SQM). Specific algorithms that can be implemented in MapReduce are discussed, such as linear regression, naive Bayes, logistic regression, and
![Modeling with Hadoop kdd2011](https://cdn-ak-scissors.b.st-hatena.com/image/square/def748950e44a79676bf388cab006ff65e27360c/height=288;version=1;width=512/https%3A%2F%2Fcdn.slidesharecdn.com%2Fss_thumbnails%2Fkdd2011tutorialfinal-110829121610-phpapp02-thumbnail.jpg%3Fwidth%3D640%26height%3D640%26fit%3Dbounds)