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Risk Bounds For Mode Clustering (1505.00482v1)

Published 3 May 2015 in math.ST, cs.LG, stat.ML, and stat.TH

Abstract: Density mode clustering is a nonparametric clustering method. The clusters are the basins of attraction of the modes of a density estimator. We study the risk of mode-based clustering. We show that the clustering risk over the cluster cores --- the regions where the density is high --- is very small even in high dimensions. And under a low noise condition, the overall cluster risk is small even beyond the cores, in high dimensions.

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