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Parameterization-free clustering with sparse data observers
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DOI：10.1016/j.is.2025.102562.png)
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Abstract
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• SDOclust shows excellent clustering in most scenarios with default parameters. • SDOclust: parameter-free, noise-resistant, able to extract non-convex clusters. • SDOclust builds highly interpretable models. • Exhaustive comparison with more than 200 datasets and 6 clustering alternatives. • Thorough discussion of the methodology of clustering in real applications.
Keywords:
Clustering
Sparse data observers
Unsupervised learning
Data analysis methodologies
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