Selection of the number of clusters via the bootstrap method
journal contributionposted on 21.08.2012 by Yixin Fang, Junhui Wang
Any type of content formally published in an academic journal, usually following a peer-review process.
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 manuscript, 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.