The Weka mailing list (firstname.lastname@example.org) is for discussions pertaining to the use of the Weka machine learning workbench.
Weka is a collection of machine learning algorithms in Java that can be used via a command-line interface, a graphical user interface, or your own Java code. Weka can be used to learn about machine learning, apply machine learning in applications, and develop new machine learning algorithms.
Implemented schemes cover decision tree inducers, rule learners, model tree generators, support vector machines, locally weighted regression, instance-based learning, bagging, boosting, stacking, and many more methods. Also included are clustering methods, association rule learners, attribute selection methods, visualization tools, and time series prediction methods. Apart from actual learning schemes, Weka also contains a large variety of tools that can be used for pre-processing datasets.
Weka is freely available under the GPL open-source license and can be obtained via http://www.cs.waikato.ac.nz/ml/.
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