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Selecting an optimal clustering solutions is a difficult problem, and there exist many data-driven validation strategies to perform this task. In this paper, we focus on a recent proposal, the BQH and BQS criteria, based on quadratic discriminant scores and bootstrap resampling. We provide more insight on these criteria, comparing them with a likelihood-based alternative and using different resampling schemes.