Apache Mahout
| Developer(s) | Apache Software Foundation |
|---|---|
| Stable release | 0.7
/ 16 June 2012 |
| Repository | |
| Written in | Java |
| Operating system | Cross-platform |
| Type | machine learning |
| License | Apache 2.0 Licence |
| Website | mahout |
Apache Mahout is an Apache project to produce free implementations of distributed or otherwise scalable machine learning algorithms on the Hadoop platform.[1][2] Mahout is a work in progress; the number of implemented algorithms has grown quickly,[3] 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.
References
- ^ "Introducing Apache Mahout". ibm.com. 2011 [last update]. Retrieved 13 September 2011.
{{cite web}}: Check date values in:|year=(help) - ^ "InfoQ: Apache Mahout: Highly Scalable Machine Learning Algorithms". infoq.com. 2011 [last update]. Retrieved 13 September 2011.
{{cite web}}: Check date values in:|year=(help) - ^ "Algorithms - Apache Mahout - Apache Software Foundation". cwiki.apache.org. 2011 [last update]. Retrieved 13 September 2011.
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External links
- Official website
- 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.
