A Note on Objective-based Rough Clustering with Fuzzy-Set Representation

DOI
  • Onishi Ken
    Department of Risk Engineering, University of Tsukuba
  • Endo Yasunori
    Faculty of Engineering, Information and Systems, University of Tsukuba

Bibliographic Information

Other Title
  • 目的関数最適化に基づくラフクラスタリングに関する一考察

Abstract

Clustering is one of the method of data analysis. Rough k-means (RKM) by Lingras et al. is one of rough clustering algorithms[3]. The method doesn’t have a clear indicator to determine the most appropriate result because it is not based on any objective functions. Therefore, a rough clustering algorithm based on optimization of an objective function was proposed[6]. This paper will propose a new rough clustering algorithm based on optimization of an objective function with fuzzy-set representation to obtain better lower approximation and estimate the effectiveness through some numerical examples.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390001205672236544
  • NII Article ID
    130005480348
  • DOI
    10.14864/fss.29.0_18
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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