Bifet, A., Holmes, G., Kirkby, R., Pfahringer, B. (2010). MOA: Massive Online Analysis. Journal of Machine Learning Research, 11, 1601-1604.
Permanent Research Commons link: http://hdl.handle.net/10289/3984
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collection of offline and online methods as well as tools for evaluation. In particular, it implements boosting, bagging, and Hoeffding Trees, all with and without Naïve Bayes classifiers at the leaves. MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, and is released under the GNU GPL license.
Massachusetts Institute of Technology Press
This article has been published in the Journal of Machine Learning Research. Copyright 2010 Albert Bifet, Geoff Holmes, Richard Kirkby and Bernhard Pfahringer.