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G-REX: A Versatile Framework for Evolutionary Data Mining
University of Borås, Sweden.
University of Borås, Sweden.
Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Cognition and Artificial Intelligence Lab (SCAI))
2008 (engelsk)Inngår i: Proceedings - IEEE International Conference on Data Mining Workshops, ICDM Workshops 2008 / [ed] Francesco Bonchi; Bettina Berendt; Fosca Giannotti; Dimitrios Gunopulos; Franco Turini; Carlo Zaniolo; Naren Ramakrishnan; Xindong Wu, IEEE, 2008, s. 971-974Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This paper presents G-REX, a versatile data mining framework based on Genetic Programming. What differs G-REX from other GP frameworks is that it doesn’t strive to be a general purpose framework. This allows G-REX to include more functionality specific to data mining like preprocessing, evaluation- and optimization methods, but also a multitude of predefined classification and regression models. Examples of predefined models are decision trees, decision lists, k-NN with attribute weights, hybrid kNN-rules, fuzzy-rules and several different regression models. The main strength is, however, the flexibility, making it easy to modify, extend and combine all of the predefined functionality. G-REX is, in addition, available in a special Weka package adding useful evolutionary functionality to the standard data mining tool Weka.

 

 

sted, utgiver, år, opplag, sider
IEEE, 2008. s. 971-974
Serie
IEEE International Conference on Data Mining Workshops, ICDMW, ISSN 2375-9232, E-ISSN 2375-9259
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URN: urn:nbn:se:his:diva-2829DOI: 10.1109/ICDMW.2008.117Scopus ID: 2-s2.0-62449143933ISBN: 978-0-7695-3503-6 (digital)OAI: oai:DiVA.org:his-2829DiVA, id: diva2:201484
Konferanse
IEEE International Conference on Data Mining Workshops, ICDM Workshops 2008, Pisa, 15 December 2008 through 19 December 2008
Tilgjengelig fra: 2009-03-04 Laget: 2009-03-04 Sist oppdatert: 2025-09-29bibliografisk kontrollert

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