Frank, E., Hall, M.A., Holmes, G., Kirkby, R., Pfahringer, B., Witten, I.H.(2005). Weka: A machine learning workbench for data mining. In O. Maimon & L. Rokach(Eds), Data Mining and Knowledge Discovery Handbook: A Complete Guide for Practitioners and Researchers(pp. 1305-1314). Berlin: Springer.
Permanent Research Commons link: https://hdl.handle.net/10289/1497
The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data preprocessing tools. The basic way of interacting with these methods is by invoking them from the command line. However, convenient interactive graphical user interfaces are provided for data exploration, for setting up large-scale experiments on distributed computing platforms, and for designing configurations for streamed data processing. These interfaces constitute an advanced environment for experimental data mining. The system is written in Java and distributed under the terms of the GNU General Public License.
The article has been published in the book: Data Mining and Knowledge Discovery Handbook. © Springer, Berlin. Used with permission. The book is available at: http://www.springer.com/978-0-387-24435-8