• DocumentCode
    441879
  • Title

    Classification methods based on bipartite graph

  • Author

    Qi, Heng-Nian ; Wang, Hang-Jun ; Jiang, Zhen-Jie ; Chen, Er-Xue

  • Author_Institution
    Sch. of Inf. Eng., Zhejiang Forestry Univ., Lin´´an, China
  • Volume
    4
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    2489
  • Abstract
    Bipartite graph is a kind of special graph. Generally, it is used for solving matching problems such as assignment problem, fault diagnosis problem and so on. But from the definition, bipartite graph has intrinsic classification implication. The paper overviews some related studies on classifications based on bipartite graph, and then presents a new classification method based on bipartite graph for homogeneous objects. It shows that objects can be classified according to the relations among them. For the relations are decided by the attributes of the objects directly or indirectly. The classification can also reveal the dependence between the relations and the attributes. The correspondent classification algorithm called Big-C is also given in the paper.
  • Keywords
    graph theory; pattern classification; Big-C classification algorithm; assignment problem; bipartite graph; fault diagnosis problem; intrinsic classification implication; special graph; Bipartite graph; Classification algorithms; Cybernetics; Fault diagnosis; Forestry; Machine learning; Optimal matching; Big-C; Bipartite graph; Classification algorithm; Classifier;
  • 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.2005.1527362
  • Filename
    1527362