Missing Clusters Indicate Poor Estimates or Guesses of a Proper Fuzzy Exponent

Authors:
Ulrich Möller
Affiliations:
Leibniz Institute for Natural Product Research and Infection Biology -, Hans Knöll Institute, 07745 Jena, Germany
Venue:
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Year:
2007

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Abstract

The term `missing cluster' (MC) is introduced as an undesirable feature of fuzzy partitions. A method for detecting persistent MCs is shown to improve the choice of proper fuzzy parameter values in fuzzy C-means clustering when compared to other methods. The comparison was based on simulated data and gene expression profiles of cancer.