On Fuzzy c-Means for Data with Tolerance

Abstract

This paper presents two new clustering algorithms which are based on the entropy regularized fuzzy c -means and can treat data with some errors. First, the tolerance is formulated and introduce into optimization problems of clustering. Next, the problems are solved using Kuhn-Tucker conditions. Last, the algorithms are constructed based on the results of solving the problems.