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On systematic hyperparameter analysis through the example of subspace clustering

In publications where a clustering method is described, the chosen hyperparameters are in many cases to our current observation empirically determined. In this work in progress we discuss and propose one approach on how hyperparameters can be systematically explored and their effects regarding the data set analyzed. We further introduce in the context of hyperparameter analysis a modified definition of the resilience term, which refers here to a subset of data points which persists to be in the same cluster over different hyperparameter settings. In order to analyze relations among different hyperparameters we further introduce the concept of dynamic intersection computing.