Weka: Practical machine learning tools and techniques with Java implementations
Ian H. Witten, Eibe Frank, Leonard E. Trigg, Mark A. Hall, Geoffrey Holmes, Sally Jo Cunningham · Research Commons (University of Waikato) · 1999
Introduction The Waikato Environment for Knowledge Analysis (Weka) is a comprehensive suite of Java class libraries that implement many state-of-the-art machine learning and data mining algorithms. Weka is freely available on the World-Wide Web and accompanies a new text on data mining [1] which documents and fully explains all the algorithms it contains. Applications written using the Weka class libraries can be run on any computer with a Web browsing capability; this allows users to apply machine learning techniques to their own data regardless of computer platform. Tools are provided for pre-processing data, feeding it into a variety of learning schemes, and analyzing the resulting classifiers and their performance. An important resource for navigating through Weka is its on-line documentation, which is automatically generated from the source. The pri