Techniques for measuring the stability of clustering: a comparative study
SIGIR '82 Proceedings of the 5th annual ACM conference on Research and development in information retrieval
Dynamic information and library processing
Dynamic information and library processing
Concepts of the cover coefficient-based clustering methodology
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
Clustering methodologies for software engineering
Advances in Software Engineering
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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.