| Title | Cluster Analyses of a Target Data Set from the IFCS Cluster Benchmark Data Repository: Introduction to the Special Issue |
| Authors | Van Mechelen, Iven and Vach, Werner |
| Year | 2019 |
| Volume | Archives of Data Science, Series B 1(1) / 2019 |
| Abstract | Stability of clustering partitions (e. g. Gfeller et al., 2005; von Luxburg, 2010) and the problem of how to define good clusters (e. g. Hennig, 2015) are recurring topics in data analysis. We present a novel approach to characterize the stability of graph clustering partitions that is based solely on the graph’s automorphism group. All in all, three formally equivalent definitions are given, each from a different point of view. Two of these conditions are exploited for the design of an algorithm for fast stability detection of a graph clustering partition. These characterizations can be perfectly combined with others in terms of an additional constraint that a “good” clustering solution must fulfill. Our propositions are likely to be generalized for other data formats than graphs, provided the automorphism group is known. |
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