• DocumentCode
    1854900
  • Title

    Data mining, unsupervised learning and Bayesian ying-yang theory

  • Author

    Xu, Lei

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
  • Volume
    4
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    2520
  • Abstract
    A number of unsupervised learning methods or algorithms have been summarized from the perspective of their potential uses in data mining. Major unsupervised learning tasks are then systematically viewed under a unified framework called Bayesian ying-yang (BYY) learning. Furthermore, it is shown systematically how the BYY learning theory can guide us not only to revisit the existing major unsupervised learning methods and results, but also to obtain a number of new methods and results
  • Keywords
    Bayes methods; data mining; neural nets; principal component analysis; unsupervised learning; Bayesian ying-yang learning; data mining; knowledge discovery; machine learning; principal component analysis; unsupervised learning; Bayesian methods; Clustering algorithms; Curve fitting; Data mining; Data visualization; Delta modulation; Neural networks; Principal component analysis; Surface fitting; Unsupervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1999. IJCNN '99. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-5529-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.1999.833469
  • Filename
    833469