Generation of Reducts Based on Nearest Neighbor Relations and Boolean Reasoning

  • Naohiro IshiiEmail author
  • Ippei Torii
  • Kazunori Iwata
  • Kazuya Odagiri
  • Toyoshiro Nakashima
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10334)


Dimension reduction of data is an important issue in the data processing and it is needed for the analysis of higher dimensional data in the application domains. Rough set is fundamental and useful to reduce higher dimensional data to lower one. 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. It is shown that nearest neighbor relation with minimal distance proposed here has a fundamental information for classification. In this paper, the nearest neighbor relation plays a fundamental role for generation of reducts using the Boolean reasoning. Then, two reduct generation methods based on the nearest neighbor relation with minimal distance are proposed here, which are derived from Boolean expression of nearest neighbor relations and their operations.


Reduct Nearest neighbor relation Indiscernibility matrix Boolean reasoning Classification 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Naohiro Ishii
    • 1
    Email author
  • Ippei Torii
    • 1
  • Kazunori Iwata
    • 2
  • Kazuya Odagiri
    • 3
  • Toyoshiro Nakashima
    • 3
  1. 1.Aichi Institute of TechnologyToyotaJapan
  2. 2.Aichi UniversityNagoyaJapan
  3. 3.Sugiyama Jyogakuen UniversityNagoyaJapan

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