Apache Mahout
Apache Mahout is an Apache project to produce free implementations of distributed or otherwise scalable machine learning algorithms on the Hadoop platform. Mahout is a work in progress; the number of implemented algorithms has grown quickly, but there are still various...
Features
- Data Mining
Tags
- big-data
- Machine Learning
- data-integration
- hadoop
- data-extraction
- time-series-data
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Apache Software Foundation Licensing
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What is Apache Mahout?
Apache Mahout is an Apache project to produce free implementations of distributed or otherwise scalable machine learning algorithms on the Hadoop platform. Mahout is a work in progress; the number of implemented algorithms has grown quickly, but there are still various algorithms missing.While Mahout's core algorithms for clustering, classification and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm, it does not restrict contributions to Hadoop based implementations. Contributions that run on a single node or on a non-Hadoop cluster are also welcomed. For example, the 'Taste' collaborative-filtering recommender component of Mahout was originally a separate project, and can run stand-alone without Hadoop. Integration with initiatives such as the Pregel-like Giraph are actively under discussion.External links EC2 AMI with Hadoop and Mahout Giraph - a Graph processing infrastructure that runs on Hadoop (see Pregel). Pregel - Google's internal graph processing platform, released details in ACM paper.