Clustering with Confidence: A Binning Approach

We present a plug-in method for estimating the cluster tree of a density. The method takes advantage of the ability to exactly compute the level sets of a piecewise constant density estimate. We then introduce clustering with confidence, an automatic pruning procedure that assesses significance of splits (and thereby clusters) in the cluster tree; the only user input required is the desired confidence level.

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