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CAKE: Confidence in Assignments via K-partition Ensembles
Aggelos Semoglou, John Pavlopoulos
Clustering is widely used for unsupervised structure discovery, yet it offers limited insight into how reliable each individual assignment is. Diagnostics, such as convergence beha…
Composite Silhouette: A Subsampling-based Aggregation Strategy
Aggelos Semoglou, Aristidis Likas, John Pavlopoulos
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…
Silhouette-Driven Instance-Weighted -means
Aggelos Semoglou, Aristidis Likas, John Pavlopoulos
Clustering is a fundamental unsupervised learning task with applications across a wide range of domains. Popular algorithms such as -means are efficient and widely used, but can…