Risk Bounds For Mode Clustering
classification
🧮 math.ST
cs.LGstat.MLstat.TH
keywords
clusteringriskdensityhighclustercoresdimensionseven
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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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