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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.
| Date | Stars |
|---|---|
| 2026-07-31 | 661 |
| 2026-08-06 | 662 |
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growth rate 0.00%/day
# MOA (Massive Online Analysis) [](https://travis-ci.org/Waikato/moa) [](https://mvnrepository.com/artifact/nz.ac.waikato.cms) [](https://hub.docker.com/r/waikato/moa) [](https://www.gnu.org/licenses/gpl-3.0) ![MOA][logo] [logo]: http://moa.cms.waikato.ac.nz/wp-content/uploads/2014/11/LogoMOA.jpg "Logo MOA" MOA is the most popular open source framework for data stream mining, with a very active growing community ([blog](http://moa.cms.waikato.ac.nz/blog/)). It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation. Related to the WEKA project, MOA is also written in Java, while scaling to more demanding problems. http://moa.cms.waikato.ac.nz/ ## Using MOA * [Getting Started](http://moa.cms.waikato.ac.nz/getting-started/) * [Building from the source](https://moa.cms.waikato.ac.nz/tutorial-6-building-moa-from-the-source/) * [Documentation](http://moa.cms.waikato.ac.nz/documentation/) * [About MOA](http://moa.cms.waikato.ac.nz/details/) MOA performs BIG DATA stream mining in real time, and large scale machine learning. MOA can be extended with new mining algorithms, and new stream generators or evaluation measures. The goal is to provide a benchmark suite for the stream mining community. ## Mailing lists * MOA users: http://groups.google.com/group/moa-users * MOA developers: http://groups.google.com/group/moa-development ## Citing MOA If you want to refer to MOA in a publication, please cite the following JMLR paper: > Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer (2010); > MOA: Massive Online Analysis; Journal of Machine Learning Research 11: 1601-1604
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:53686e34f205996d, llm:Repository description and README: 'MOA is an open source framework for Big Data stream mining... includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.' Topics: data-stream-mining, machine-learning, streaming-algorithms.
matched fp:53686e34f205996d, llm:Repository description and README: 'MOA is an open source framework for Big Data stream mining... includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.' Topics: data-stream-mining, machine-learning, streaming-algorithms.
matched fp:53686e34f205996d, llm:Repository description and README: 'MOA is an open source framework for Big Data stream mining... includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.' Topics: data-stream-mining, machine-learning, streaming-algorithms.