Different Algorithms and Variations of Possibilistic Clustering

• Miyamoto Sadaaki

  University of Tsukuba

• Kuroda Youhei

  University of Tsukuba

• Inokuchi Ryo

  University of Tsukuba

Abstract

Different algorithms of possibilistic clustering are overviewed. A general formulation of possiblistic clustering is given with a new constraint which generalizes the original one. Several methods of possibilistic clustering are derived by specifying different functions in the general formulation. Theoretical properties are overviewed whereby a cluster fusion algorithm is proposed. A variation of the present method enables handling of data with weights. Numerical examples are shown.

Journal

• SCIS & ISIS

  SCIS & ISIS 2006 (0), 1655-1660, 2006

  Japan Society for Fuzzy Theory and Intelligent Informatics

Keywords

• possibilistic clustering
• fuzzy c-means
• algorithm

Details

• CRID: 1390001205590435328
• NII Article ID: 130004672407
• DOI: 10.14864/softscis.2006.0.1655.0
• Text Lang: en
• Data Source:
  • JaLC
  • CiNii Articles
• Abstract License Flag: Disallowed