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Title: Resampling methods for exploring cluster stability Authors:  Friedrich Leisch - Universitaet fuer Bodenkultur Vienna (Austria) [presenting]
Abstract: Model diagnostic for cluster analysis is still a developing field because of its exploratory nature. Numerous indices have been proposed in the literature to evaluate goodness-of-fit, but no clear winner that works in all situations has been found yet. Derivation of (asymptotic) distribution properties is not possible in most cases. Resampling schemes provide an elegant framework to computationally derive the distribution of interesting quantities describing the quality of a partition. Special emphasis will be given to the stability of a partition, i.e., given a new sample from the same population, how likely is it to obtain a similar clustering? Another application is to systematically compare partitions with a growing number of clusters to assess which clusters are stable and found repeatedly even when the number of clusters increases.