The silhouette coefficient is a metric used to measure the quality of clusters created by clustering algorithms. It evaluates how similar an object is to its own cluster compared to other clusters, providing insight into the appropriateness of the clustering method used. A high silhouette coefficient indicates that the object is well clustered, while a low score suggests that the object may be in the wrong cluster, making it a crucial tool for assessing the effectiveness of clustering in both supervised and unsupervised learning contexts.
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