• DocumentCode
    3511106
  • Title

    Research and Implement of Classification Rule Mining Algorithm Based on Attribute Reduction

  • Author

    Yin, Shiqun ; Qiu, Yuhui ; Zhong, Chengwen ; Zhou, Jifu

  • Author_Institution
    Fac. of Comput. & Inf. Sci., Southwest Univ., Chongqing
  • fYear
    2007
  • fDate
    21-25 Sept. 2007
  • Firstpage
    5601
  • Lastpage
    5604
  • Abstract
    This paper brings up a new classification algorithm of data mining (CRMA) in any scale relation database. Based on rough set theory it divides relation table into several equivalence class based on attribute values, calculates information capacity in decision factor of the every condition attribution, eliminates redundancy attributions, and erases repeat units. Then classification rules can be obtained through strong equivalence class which relation table was reduced. It overcomes the redundancy nature, complicated nature and unfit nature to big capacity data or increment data of some classification algorithm at present. It has higher efficiency and widespread application perspective in large and incremental databases. The mining algorithm and an example are discussed in details.
  • Keywords
    classification; data mining; relational databases; rough set theory; attribute reduction; classification rule mining algorithm; data mining; decision factor; equivalence class; relation database; rough set theory; Classification algorithms; Classification tree analysis; Data mining; Databases; Decision making; Electronic mail; High performance computing; Information science; Iterative algorithms; Set theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1311-9
  • Type

    conf

  • DOI
    10.1109/WICOM.2007.1372
  • Filename
    4341147