A new subsampling score, S4, selects the number of clusters and the feature-sparsity parameter together in sparse K-means and outperforms gap-statistic and prediction-strength extensions in simulations and nine real datasets.
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Simultaneous Estimation of Number of Clusters and Feature Sparsity in Clustering High-Dimensional Data
A new subsampling score, S4, selects the number of clusters and the feature-sparsity parameter together in sparse K-means and outperforms gap-statistic and prediction-strength extensions in simulations and nine real datasets.