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Recently several papers studied resampling approaches to determine the number of clusters in prototype-based clustering. The core idea underlying these approaches is that with the right choice for the number of clusters basically the same cluster structures should be obtained from subsamples of the given data set, while a wrong choice should produce considerably varying cluster structures. In this paper we investigate whether these approaches can be transferred to fuzzy clustering. It turns out that they are applicable to fuzzy clustering as well, but that not all relative cluster evaluation measures that work for crisp clustering can also be used for fuzzy clustering.