Generalized density clustering
Alessandro Rinaldo, Larry Wasserman
The Annals of Statistics · 2010 · Volume 38 · Issue 5
Abstract
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.
Keywords
62G07, 62H30, Density clustering, kernel density estimation
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