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cs.LG2025
Shapley-Inspired Feature Weighting in -means with No Additional Hyperparameters
Richard J. Fawley, Renato Cordeiro de Amorim
Clustering algorithms often assume all features contribute equally to the data structure, an assumption that usually fails in high-dimensional or noisy settings. Feature weighting…
cs.LG2025
Scalable unsupervised feature selection via weight stability
Xudong Zhang, Renato Cordeiro de Amorim
Unsupervised feature selection is critical for improving clustering performance in high-dimensional data, where irrelevant features can obscure meaningful structure. In this work,…