• DocumentCode
    2328746
  • Title

    The mining of classification rules based on multiple extended concept lattices

  • Author

    Hu, Xue-Gang ; Chen, Hui ; Ma, Feng

  • Author_Institution
    Sch. of Comput. & Inf., Hefei Univ. of Technol., China
  • Volume
    4
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    2063
  • Abstract
    Mining classification rules is an important research area in data mining. Distributed data mining is one of the important research fields. So inducing classification rules from multiple data sources and amalgamating rules become the hotspot. The extended concept lattice is the extending of Galois concept lattice, which is effective for mining classification rules. In this paper, mining classification rules based on multiple extended concept lattices is described, the method of amalgamating rules is discussed and proved by theory and experiment.
  • Keywords
    data mining; knowledge representation; Galois concept lattice; classification rule mining; data mining; multiple extended concept lattice; Cybernetics; Data mining; Electronic mail; Lattices; Machine learning; Supervised learning; Classification Rule; Data Mining; Extended Concept Lattice;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527285
  • Filename
    1527285