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A Density-Sensitive Hierarchical Clustering Method

Author

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  • Álvaro Martínez-Pérez

    (Universidad de Castilla-La Mancha)

Abstract

We define a hierarchical clustering method: α-unchaining single linkage or SL(α). The input of this algorithm is a finite space with a distance function and a certain parameter α. 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, SL*(α), 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.

Suggested Citation

  • Álvaro Martínez-Pérez, 2018. "A Density-Sensitive Hierarchical Clustering Method," Journal of Classification, Springer;The Classification Society, vol. 35(3), pages 481-510, October.
    • Handle: RePEc:spr:jclass:v:35:y:2018:i:3:d:10.1007_s00357-018-9266-x
    DOI: 10.1007/s00357-018-9266-x
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