X-means clustering
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In statistics and data mining, X-means clustering is a variation of k-means clustering that refines cluster assignments by repeatedly attempting subdivision, and keeping the best resulting splits, until some criterion is reached.[1] The Bayesian information criterion is used to make the splitting decision.[2]
References
- ^ "X-means: Extending K-means with Efficient Estimation of the Number of Clusters" (PDF). Retrieved 2016-08-16.
- ^ "The X-Alter algorithm : a parameter-free method to perform unsupervised clustering" (PDF). Retrieved 2016-08-16.