Clustering with the Average Silhouette Width
The Average Silhouette Width (ASW; Rousseeuw (1987)) is a popular cluster validation index to estimate the number of clusters. Here we address the question whether it also is suitable as a general objective function to be optimized for finding a clustering. We will propose two algorithms (the standard version OSil and a fast version FOSil) and compare them with existing clustering methods in an extensive simulation study covering the cases of a known and unknown number of clusters. Real data sets are also analysed, partly exploring the use of the new methods with non-Euclidean distances. We will also show that the ASW satisfies some axioms that have been proposed for cluster quality functions (Ackerman and Ben-David (2009)). The new methods prove useful and sensible in many cases, but some weaknesses are also highlighted. These also concern the use of the ASW for estimating the number of clusters together with other methods, which is of general interest due to the popularity of the ASW for this task.
Code (0)
등록된 구현이 없습니다.
Tasks
ClusteringSimilar Papers 제목 키워드 기반
An upper bound on the silhouette evaluation metric for clustering
The silhouette coefficient quantifies, for each observation, the balance between within-cluster cohesion and between-cluster separation, taking values in the range [-1,1]. The average silhouette width (ASW) is a widely u…
An agglomerative hierarchical clustering method by optimizing the average silhouette width
An agglomerative hierarchical clustering (AHC) framework and algorithm named HOSil based on a new linkage metric optimized by the average silhouette width (ASW) index is proposed. A conscientious investigation of various…
ClusteringInitialization methods for optimum average silhouette width clustering
A unified clustering approach that can estimate number of clusters and produce clustering against this number simultaneously is proposed. Average silhouette width (ASW) is a widely used standard cluster quality index. A …
ClusteringRevisiting Silhouette Aggregation
Silhouette coefficient is an established internal clustering evaluation measure that produces a score per data point, assessing the quality of its clustering assignment. To assess the quality of the clustering of the who…
ClusteringComposite Silhouette: A Subsampling-based Aggregation Strategy
Determining the number of clusters is a central challenge in unsupervised learning, where ground-truth labels are unavailable. The Silhouette coefficient is a widely used internal validation metric for this task, yet its…