NN-EVCLUS: neural network-based evidential clustering

DOI10.1016/j.ins.2021.05.011zbMath1528.68372arXiv2009.12795MaRDI QIDQ6092096

Thierry Denoeux

Publication date: 23 November 2023

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2009.12795

zbMATH Keywords

Dempster-Shafer theoryunsupervised learningbelief functionsevidence theorysemi-supervised learningconstrained clustering

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Cites Work

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• CECM: constrained evidential \(C\)-means algorithm
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• Fuzzy sets as a basis for a theory of possibility
• Modern multidimensional scaling: theory and applications
• Calibrated model-based evidential clustering using bootstrapping
• Objective function-based rough membership C-means clustering
• Integrating rough set principles in the graded possibilistic clustering
• ECM: An evidential version of the fuzzy \(c\)-means algorithm
• Some refinements of rough \(k\)-means clustering
• Fuzzy clustering of mixed data
• Finding Groups in Data
• Constructing a High-Dimensional k NN-Graph Using a Z-Order Curve

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