Risk Bounds For Mode Clustering
Martin Azizyan, Yen‐Chi Chen, Aarti Singh, Larry Wasserman · arXiv (Cornell University) · 2015
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.