MOA: Massive Online Analysis

Abstract

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 Naı̈ve Bayes classifiers… (More)

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@article{Bifet2010MOAMO, title={MOA: Massive Online Analysis}, author={Albert Bifet and Geoff Holmes and Richard Kirkby and Bernhard Pfahringer}, journal={Journal of Machine Learning Research}, year={2010}, volume={11}, pages={1601-1604} }