Estimating the Number of Clusters in a Data Set Via the Gap Statistic

Robert Tibshirani1, Guenther Walther1, Trevor Hastie1
1Stanford University - USA > > > >

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Summary 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.

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