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Clustering with the Average Silhouette Width
The new methods prove useful and sensible in many cases, but some weaknesses are also highlighted.
Initialization methods for optimum average silhouette width clustering
Simulation reveals that OSil algorithm has shown superior performance in terms of clustering quality than all clustering methods included in the study.
An agglomerative hierarchical clustering method by optimizing the average silhouette width
HOSil has shown better clustering quality for a range of artificial and real world data structures as compared to k-means, PAM, single, complete, average, Ward, McQuitty, spectral, model-based, and several estimation methods.
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