About: Massive Online Analysis (MOA) is a real time analytic tool for data streams. It 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 Naive Bayes classifiers at the leaves. MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, and it is released under the GNU GPL license.Changes:
New version November 2013
About: LIBOL is an open-source library with a family of state-of-the-art online learning algorithms for machine learning and big data analytics research. The current version supports 16 online algorithms for binary classification and 13 online algorithms for multiclass classification.Changes:
In contrast to our last version (V0.2.3), the new version (V0.3.0) has made some important changes as follows:
• Add a template and guide for adding new algorithms;
• Improve parameter settings and make documentation clear;
• Improve documentation on data formats and key functions;
• Amend the "OGD" function to use different loss types;
• Fixed some name inconsistency and other minor bugs.
About: MATLAB toolbox for advanced Brain-Computer Interface (BCI) research.Changes:
Initial Announcement on mloss.org.