• DocumentCode
    2632894
  • Title

    A Novel Fuzzy Based Classification for Data Mining Using Fuzzy Discretization

  • Author

    Mehta, Rupa G. ; Rana, Dipti P. ; Zaveri, Mukesh A.

  • Author_Institution
    Comput. Eng. Dept., S.V. Nat. Inst. of Technol., Surat, India
  • Volume
    3
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    713
  • Lastpage
    717
  • Abstract
    Data mining is a process to discover useful, possibly unexpected, patterns from the large set of data and widely used in the large information processing applications. Classification is used to classify the data into a set of classes based on some attributes for further processing. Real world application contains very large,imprecise and noisy data. In this case, the knowledge representation need some linguistic term instead of discrete value. In such a scenario fuzzy logic based processing is a natural choice. In this paper, we propose an algorithm for classification using fuzzy approach, which performs class dependent fuzzy discretization.The continuous numeric data is converted in linguistic form which helps in fuzzy classification. The proposed method is compared with standard non-fuzzy discretization techniques where class-attribute relationship is not considered and intervals are predefined. Simulation results show the improved performance of the proposed method.
  • Keywords
    data mining; fuzzy logic; pattern classification; class-attribute relationship; continuous numeric data; data classification; data mining; fuzzy based classification; fuzzy classification; fuzzy logic; information processing applications; knowledge representation; nonfuzzy discretization techniques; Classification tree analysis; Computer science; Data engineering; Data mining; Delta modulation; Fuzzy logic; Fuzzy sets; Information processing; Knowledge representation; Partitioning algorithms; Data Mining (DM); Fuzzy based Classification; Fuzzy discretization; Interval discretization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.294
  • Filename
    5170934