Weka (machine learning)

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http://www.cs.waikato.ac.nz/ml/weka/index.html
WEKA
Type Open Source
Industry Machine Learning
Founded 1993
Headquarters Hamilton, New Zealand
Key people Ian H. Witten, Eibe Frank
Investors Pentaho Inc.
Related Certifications Certificate in Machine Learning Industry Overview


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[1]. Weka is freely available on the World-Wide Web and accompanies a new text on data mining which documents and fully explains all the algorithms it contains. It is free software licensed under the GNU General Public License. WEKA is a popular suite of machine learning software written in Java, developed at the University of Waikato, New Zealand.

History

  • In 1993, the University of Waikato in New Zealand began development of the original version of Weka, which became a mix of Tcl/Tk, C, and Makefiles.[2]
  • The original non-Java version of Weka was a Tcl/Tk front-end to (mostly third-party) modeling algorithms implemented in other programming languages, plus data preprocessing utilities in C, and a Makefile-based system for running machine learning experiments. This original version was primarily designed as a tool for analyzing data from agricultural domains.[3]
  • In 1997, WEKA was redeveloped from scratch in Java, including implementations of modeling algorithms.[4]
  • The 2005 ACM SIGKDD Service Award was presented to the Weka team for their development of the freely-available Weka Data Mining Software.[5]
  • In 2006, Pentaho Corp., creator of the world's most popular open source business intelligence (BI) suite, announced the acquisition of Weka open source data mining project.[6]
  • WEKA was ranked among Infoworld's 'Top 11 open source tools to make the most of machine learning'.[7]

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  1. http://www.cs.waikato.ac.nz/~ml/publications/1999/99IHW-EF-LT-MH-GH-SJC-Tools-Java.pdf
  2. https://www.cs.waikato.ac.nz/~ml/publications/1994/Holmes-ANZIIS-WEKA.pdf
  3. http://www.cs.waikato.ac.nz/~ml/publications/1995/Garner95-imlc95.pdf
  4. http://www.cs.waikato.ac.nz/~ml/publications/1999/99IHW-EF-LT-MH-GH-SJC-Tools-Java.pdf
  5. http://www.kdnuggets.com/news/2005/n13/2i.html
  6. http://www.businesswire.com/news/home/20060919006066/en/Pentaho-Acquires-Weka-Project-Worlds-Popular-Open
  7. http://www.infoworld.com/article/2853707/machine-learning/11-open-source-tools-machine-learning.html#slide10

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