DocumentCode :
2132091
Title :
G-REX: A Versatile Framework for Evolutionary Data Mining
Author :
Konig, Rikard ; Johansson, Ulf ; Niklasson, Lars
Author_Institution :
Univ. of Boras, Boras
fYear :
2008
fDate :
15-19 Dec. 2008
Firstpage :
971
Lastpage :
974
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.
Keywords :
data mining; decision trees; fuzzy set theory; genetic algorithms; regression analysis; G-REX; Weka; decision lists; decision trees; evolutionary data mining; fuzzy-rules; genetic programming; hybrid kNN-rules; regression models; Conferences; Data mining; Decision trees; Genetic programming; Graphical user interfaces; Java; Measurement; Optimization methods; Packaging; Regression tree analysis; Data Mining; Framework; Genetic Programming; Representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining Workshops, 2008. ICDMW '08. IEEE International Conference on
Conference_Location :
Pisa
Print_ISBN :
978-0-7695-3503-6
Electronic_ISBN :
978-0-7695-3503-6
Type :
conf
DOI :
10.1109/ICDMW.2008.117
Filename :
4734030
Link To Document :
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