• DocumentCode
    401865
  • Title

    The information granulation in discretization

  • Author

    Wang, Li-hong ; Zhang, Shu-cui ; Fan, Hui ; Wu, Geng-feng

  • Author_Institution
    Sch. of Comput. Sci. and Technol., Shanghai Univ., China
  • Volume
    5
  • fYear
    2003
  • fDate
    2-5 Nov. 2003
  • Firstpage
    2620
  • Abstract
    Discretization is a vehicle of abstraction that supports a conversion of clouds of numeric data into more tangible information granules, which can be represented as hyper-boxes in R". A partial ordering of all discretization schemes for a given information table is defined to describe the relative granularity. All discretized tables form a hierarchical structure, representing the information table under different granulation. The granule-based entropy is defined to measure the information change in discretization. With meet and join operations, the partially ordered set becomes a lattice named discretization lattice, which is a Boolean algebra.
  • Keywords
    Boolean algebra; data mining; learning (artificial intelligence); rough set theory; Boolean algebra; discretization lattice; discretized tables; granule based entropy; hierarchical structure; hyper boxes; information granulation; numeric data conversion; partial ordering; partially ordered set; relative granularity; Boolean algebra; Clouds; Computer science; Data analysis; Data mining; Entropy; Information analysis; Lattices; Machine learning; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2003 International Conference on
  • Print_ISBN
    0-7803-8131-9
  • Type

    conf

  • DOI
    10.1109/ICMLC.2003.1259971
  • Filename
    1259971