MOA – software environment for data stream mining

MOA (Massive Online Analysis) is a popular open source for software environment for implementing algorithms and running experiments for online learning from evolving data streams.

It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.

MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, which is an award-winning open-source workbench containing implementations of a wide range of batch machine learning methods.

The software is developed in the Java programming language.

Features include:

• Classification:
  • Bayesian classifiers.
    • Naive Bayes.
      Naive Bayes Multinomial.
  •  Decision trees classifiers:
    • Decision Stump.
    • Hoeffding Tree.
    • Hoeffding Option Tree.
    • Hoeffding Adaptive Tree.
  •  Meta classifiers:
    • Bagging.
    • Boosting.
    • Bagging using ADWIN.
    • Bagging using Adaptive-Size Hoeffding Trees.
    • Perceptron Stacking of Restricted Hoeffding Trees.
    • Leveraging Bagging.
    • Online Accuracy Updated Ensemble.
  • Function classifiers:
    • Perceptron.
    • Stochastic gradient descent (SGD).
    • Pegasos.
  •  Drift classifiers.
    • Self-Adjusting Memory.
    • Probabilistic Adaptive Windowing.
  •  Multi-label classifiers.
  • Active learning classifiers .
•  Regression.
  • FIMTDD.
  • AMRules.
• Clustering.
  • StreamKM++.
  • CluStream.
  • ClusTree.
  • D-Stream.
  • CobWeb.
• Outlier detection.
  • STORM.
  • Abstract-C.
  • COD.
  • MCOD.
  • AnyOut.
• Recommender systems.
  • BRISMFPredictor.
• Frequent pattern mining.
  • Itemsets.
  • Graphs.
• Change detection algorithms.

Website: moa.cms.waikato.ac.nz
Support: Documentation, Mailing List (Users), Mailing List (Developers), GitHub Code Repository
Developer: University of Waikato
License: GNU General Public License v3.0

MOA is written in Java. Learn Java with our recommended free books and free tutorials.

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