A convergence theorem for the fuzzy subspace clustering (FSC) algorithm

  • Authors:
  • G. Gan;J. Wu

  • Affiliations:
  • Department of Mathematics and Statistics, York University, Toronto, Ont., Canada M3J 1P3;Department of Mathematics and Statistics, York University, Toronto, Ont., Canada M3J 1P3

  • Venue:
  • Pattern Recognition
  • Year:
  • 2008

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Abstract

We establish the convergence of the fuzzy subspace clustering (FSC) algorithm by applying Zangwill's convergence theorem. We show that the iteration sequence produced by the FSC algorithm terminates at a point in the solution set S or there is a subsequence converging to a point in S. In addition, we present experimental results that illustrate the convergence properties of the FSC algorithm in various scenarios.