Approaches for measuring the stability of clustering methods

Among the significant factors in assessing the suitability of a clustering technique to a given application is its stability; that is, how sensitive the algorithm is to perturbations in the input data. A number of techniques that appear to be suitable for measuring the stability of clustering have been published in the literature. When these techniques are closely examined, a number of generic approaches emerge. This note reviews these approaches and provides a classification of the various techniques appearing in the literature in terms of the approaches identified.