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Estimating the number of clusters in a data set via the gap statistic

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  • Robert Tibshirani
  • Guenther Walther
  • Trevor Hastie

Abstract

We propose a method (the ‘gap statistic’) for estimating the number of clusters (groups) in a set of data. The technique uses the output of any clustering algorithm (e.g. K‐means or hierarchical), comparing the change in within‐cluster dispersion with that expected under an appropriate reference null distribution. Some theory is developed for the proposal and a simulation study shows that the gap statistic usually outperforms other methods that have been proposed in the literature.

Suggested Citation

  • Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
  • Handle: RePEc:bla:jorssb:v:63:y:2001:i:2:p:411-423
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    File URL: https://doi.org/10.1111/1467-9868.00293
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