We study generalized density-based clustering in which sharply defined
clusters such as clusters on lower-dimensional manifolds are allowed. We show
that accurate clustering is possible even in high dimensions. We propose two
data-based methods for choosing the bandwidth and we study the stability
properties of density clusters. We show that a simple graph-based algorithm
successfully approximates the high density clusters.Comment: Published in at http://dx.doi.org/10.1214/10-AOS797 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org