- author = "Rikard Konig and Ulf Johansson and Lars Niklasson",
- title = "{G-REX}: A Versatile Framework for Evolutionary Data Mining",
- booktitle = "IEEE International Conference on Data Mining Workshops, ICDMW '08",
- year = "2008",
- month = "15-19 " # dec,
- address = "Pisa, Italy",
- pages = "971--974",
- keywords = "genetic algorithms, genetic programming, G-REX, Weka, decision lists, decision trees, evolutionary data mining, fuzzy-rules, hybrid kNN-rules, regression models, data mining, decision trees, fuzzy set theory, regression analysis",
- isbn13 = "978-0-7695-3503-6",
-
DOI = "
doi:10.1109/ICDMW.2008.117",
-
code_url = "
https://sites.google.com/site/grexunleashed/",
- size = "4 pages",
- abstract = "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.",
-
notes = "University of Boras, Sweden
Also known as \cite{4734030}",
