A density-sensitive hierarchical clustering method

Abstract

We define a hierarchical clustering method: $\alpha$-unchaining single linkage or $SL(\alpha )$. The input of this algorithm is a finite metric space and a certain parameter $\alpha$. This method is sensitive to the density of the distribution and offers some solution to the so called chaining effect. We also define a modified version, $S{L}^{\ast }(\alpha )$, to treat the chaining through points or small blocks. We study the theoretical properties of these methods and offer some theoretical background for the treatment of chaining effects.

arXiv comment25 pages, 14 figures