• 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