A tolerance concept in data clustering

Abstract

This paper introduces the concept of tolerance space as an abstract model of data clustering. The similarity in the model is represented by a relation with both reflexivity and symmetry, called a tolerance relation. Three types of clusterings based on a tolerance relation are introduced: maximal complete similarity clustering, representative clustering, and closure clustering. This paper also discusses experiments on unsupervised learning, in which Hamming distance is used to define a family of tolerance relations. © Springer-Verlag 2003.