• DocumentCode
    397862
  • Title

    A clustering application method based on mix type variables in social system appraisement

  • Author

    Xiao-hong, Liu ; Yang, Xu ; Ke-yun, Qin ; Zheng, Pei

  • Author_Institution
    Intelligent Control Dev. Center, Southwest Jiaotong Univ., Chengdu, China
  • Volume
    3
  • fYear
    2003
  • fDate
    5-8 Oct. 2003
  • Firstpage
    2857
  • Abstract
    Clustering is one of major function in data mining. Social system appraisement is faced with random variable and fuzzy variable, in order to solve the clustering of the mix type variables, this paper puts forward a clustering application method. The major thought of this method as follows: on the foundation of screening in advance for data source, classifies data variable according to whether belong to random variable or fuzzy variable. Random variable is determined by posterior probability distribution through Bayes study theory, and made it carry out clustering with the method of not random variable with posterior probability distribution as the weight of random variable. For fuzzy variable, the equivalence matrix is established according to the system clustering method of fuzzy relation, and converted it into Equivalence matrix to carry out clustering.
  • Keywords
    Bayes methods; data mining; fuzzy set theory; inference mechanisms; pattern clustering; probability; random functions; social sciences computing; uncertainty handling; Bayes study theory; D-S evidence theory; Dempster-Shafer evidence theory; clustering application method; data mining; equivalence matrix; fuzzy variable; mix type variables; probability distribution; random variable; social system appraisement; Appraisal; Clustering algorithms; Data mining; Fuzzy systems; Humans; Intelligent control; Matrix converters; Partitioning algorithms; Probability distribution; Random variables;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2003. IEEE International Conference on
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-7952-7
  • Type

    conf

  • DOI
    10.1109/ICSMC.2003.1244319
  • Filename
    1244319