Selection of the number of clusters via the bootstrap method

Yixin Fang and Junhui Wang

Computational Statistics & Data Analysis, 2012, vol. 56, issue 3, 468-477

Abstract: Here the problem of selecting the number of clusters in cluster analysis is considered. Recently, the concept of clustering stability, which measures the robustness of any given clustering algorithm, has been utilized in Wang (2010) for selecting the number of clusters through cross validation. In this paper, an estimation scheme for clustering instability is developed based on the bootstrap, and then the number of clusters is selected so that the corresponding estimated clustering instability is minimized. The proposed selection criterion’s effectiveness is demonstrated on simulations and real examples.

Keywords: Cluster analysis; K-means; Spectral clustering; Stability (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (15)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:56:y:2012:i:3:p:468-477

DOI: 10.1016/j.csda.2011.09.003

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