Estimating the Number of Clusters in a Data Set Via the Gap Statistic
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ID: 289431
2001
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Abstract
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.
| Reference Key |
openalex_W2071949631
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|---|---|
| Authors | Robert Tibshirani, Guenther Walther, Trevor Hastie |
| Journal | Journal of the Royal Statistical Society Series B (Statistical Methodology) |
| Year | 2001 |
| DOI |
10.1111/1467-9868.00293
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| URL | |
| Keywords | Keywords not found |
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