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How to cluster colors using weka jar in java code#
You can even distribute it commercially, but you must disclose the source code or obtain a commercial license. Weka is distributed under the GNU General Public License (GNU GPL), which means that you can copy, distribute, and modify it as long as you track changes in source files and keep it under GNU GPL. Graphical interfaces are well suited for exploring your data, while the Java API allows you to develop new machine learning schemes and use the algorithms in your applications. Ĭurrently, Weka contains 267 algorithms in total: data preprocessing (82), attribute selection (33), classification and regression (133), clustering (12), and association rules mining (7). It features a rich graphical user interface, command-line interface, and Java API. It is a general purpose library that is able to solve a wide variety of machine learning tasks, such as classification, regression, and clustering.
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Waikato Environment for Knowledge Analysis (WEKA) is a machine learning library that was developed at the University of Waikato, New Zealand, and is probably the most well-known Java library. In this article, we will review the major libraries and platforms, the kind of problems they can solve, the algorithms they support, and the kind of data they can work with. There are over 70 Java-based open source machine learning projects listed on the website, and probably many more unlisted projects live at university servers, GitHub, or Bitbucket.