• DocumentCode
    1796492
  • Title

    Generation of reducts based on nearest neighbor relation

  • Author

    Ishii, Naohiro ; Torii, Ippei ; Nakashima, Takayoshi ; Iwata, Keiji

  • Author_Institution
    Dept. of Inf. Sci., Aichi Inst. of Technol., Toyota, Japan
  • fYear
    2014
  • fDate
    June 30 2014-July 2 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Dimension reduction of data is an important theme in the data processing and on the web to represent and manipulate higher dimensional data. Rough set is fundamental and useful to process higher dimensional data. Reduct in the rough set is a minimal subset of features, which has the same discernible power as the entire features in the higher dimensional scheme. Nearest neighbor relation between different classes has a basic information for classification. We propose here a reduct generation method based on the nearest neighbor relation. To characterize the classification ability of reducts, we develop a new graph mapping method of the nearest neighbor based on reducts and weighted modified reducts for the classification with higher accuracy.
  • Keywords
    graph theory; pattern classification; rough set theory; data processing; dimension reduction; graph mapping method; higher dimensional data; nearest neighbor relation; reduct generation method; rough set theory; Absorption; Accuracy; Data analysis; Educational institutions; Equations; Sufficient conditions; classification; mapping ofreducts; nearest neighbor relation; reduct; reduct eneration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2014 15th IEEE/ACIS International Conference on
  • Conference_Location
    Las Vegas, NV
  • Type

    conf

  • DOI
    10.1109/SNPD.2014.6888692
  • Filename
    6888692