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The WEKA data mining software: an update

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Hall, Mark, Frank, Eibe, Holmes, Geoffrey, Pfahringer, Bernhard, Reutemann, Peter, Witten, Ian H.·2009·ACM SIGKDD Explorations Newsletter

DOI 10.1145/1656274.1656278

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Abstract

More than twelve years have elapsed since the first public release of WEKA. In that time, the software has been rewritten entirely from scratch, evolved substantially and now accompanies a text on data mining [35]. These days, WEKA enjoys widespread acceptance in both academia and business, has an active community, and has been downloaded more than 1.4 million times since being placed on Source-Forge in April 2000. This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.

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Authors: Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H.
Affiliations: Pentaho Corporation, Orlando, FL
University of Waikato (NZ)
ORCID: Frank, Eibe
Holmes, Geoffrey
Pfahringer, Bernhard
Reutemann, Peter
Witten, Ian H.
Venue: ACM SIGKDD Explorations Newsletter
Publisher: Association for Computing Machinery (ACM)
Published: 2009-11-16
Volume: 11
Issue: 1
Pages: 10-18
ISSN: 1931-0145 (ISSN-L)
1931-0153
DOI: 10.1145/1656274.1656278
OpenAlex: W2133990480
Cited by: 17,750
References: 37
Citations by year: 2026: 93 · 2025: 198 · 2024: 252 · 2023: 342 · 2022: 473 · 2021: 742 · 2020: 949 · 2019: 1162 · 2018: 1382 · 2017: 1550 · 2016: 2009 · 2015: 2093 · 2014: 2031 · 2013: 1714 · 2012: 1353
FWCI: 2427.11
Type: journal article
Language: en
Open access: green
hdl.handle.net
Licence: www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations: ACM SIGKDD Explorations Newsletter (publishedVersion)
Research Commons (University of Waikato) (submittedVersion)
Topics: Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Data Classification
Keywords: WEKA, data mining tools, software release history, open source software

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The WEKA data mining software: an update

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