Fuzzy c-Means for Data with Tolerance Defined as Hyper-Rectangle

  • Authors:

  • Yasushi Hasegawa;Yasunori Endo;Yukihiro Hamasuna;Sadaaki Miyamoto

  • Affiliations:

  • Graduate School of Systems and Information Engineering, University of Tsukuba, Japan;Department of Risk Engineering, Faculty of Systems and Information Engineering, University of Tsukuba, Japan;Graduate School of Systems and Information Engineering, University of Tsukuba, Japan;Department of Risk Engineering, Faculty of Systems and Information Engineering, University of Tsukuba, Japan

  • Venue:
  • MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

The paper presents some new clustering algorithms which are based on fuzzy c-means. The algorithms can treat data with tolerance defined as hyper-rectangle. First, the tolerance is introduced into optimization problems of clustering. This is generalization of calculation errors or missing values. Next, the problems are solved and some algorithms are constructed based on the results. Finally, usefulness of the proposed algorithms are verified through numerical examples.