Risk Bounds For Mode Clustering
classification
🧮 math.ST
cs.LGstat.MLstat.TH
keywords
clusteringriskdensityhighclustercoresdimensionseven
pith:C5WTVNSS Add to your LaTeX paper
What is a Pith Number?\usepackage{pith}
\pithnumber{C5WTVNSS}
Prints a linked pith:C5WTVNSS badge after your title and writes the identifier into PDF metadata. Compiles on arXiv with no extra files. Learn more
read the original 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.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.