# Strong Consistency for a Class of Adaptive Clustering Procedures

@inproceedings{Jaffe2022StrongCF, title={Strong Consistency for a Class of Adaptive Clustering Procedures}, author={Adam Quinn Jaffe}, year={2022} }

. We introduce a class of clustering procedures which includes k means and k -medians, as well as variants of these where the domain of the cluster centers can be chosen adaptively (for example, k -medoids) and where the number of cluster centers can be chosen adaptively (for example, accord- ing to the elbow method). In the non-parametric setting and assuming only the ﬁniteness of certain moments, we show that all clustering procedures in this class are strongly consistent under IID samples…

## One Citation

### Fr\'echet Mean Set Estimation in the Hausdorff Metric, via Relaxation

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