A Generalized Sparse Fuzzy Clustering Framework with Automated Cluster Cardinality Estimation Ability

arXiv cs.AINovember 3, 2026en

arXiv:2611.00159v1 Announce Type: new Abstract: Fuzzy clustering provides a robust framework for handling ambiguous and overlapping data boundaries, yet its traditional formulation generates entirely dense membership assignments that limit noise resilience and prevent estimating the true number of clusters, when it is unknown. To address these limitations, we introduce in this paper the Generalized Sparse Fuzzy Clustering (GSFC) framework, which incorporates a continuous sparsity penalty into the fuzzy objective function. Because closed-form solutions are precluded by the simultaneous presence of fuzzifier and sparsity exponents, we propose an efficient primal-dual bisection search coupled w

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