On possibilistic clustering with repulsion constraints for imprecise data

DOI10.1016/j.ins.2013.04.008zbMath1321.62069OpenAlexW2066798080MaRDI QIDQ497539

Maria Brigida Ferraro, Paolo E. Giordani

Publication date: 24 September 2015

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

Full work available at URL: https://doi.org/10.1016/j.ins.2013.04.008

zbMATH Keywords

fuzzy datacluster analysispossibilistic approachrepulsion term

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Multivariate analysis and fuzziness (62H86)

Related Items (9)

Fuzziness in data analysis: towards accuracy and robustness ⋮ A spatial-type interval-valued median for random intervals ⋮ Possibilistic and fuzzy clustering methods for robust analysis of non-precise data ⋮ Attraction-repulsion clustering: a way of promoting diversity linked to demographic parity in fair clustering ⋮ Possibilistic fuzzy c-means with partial supervision ⋮ Evolving possibilistic fuzzy modelling ⋮ A fuzzy clustering approach for fuzzy data based on a generalized distance ⋮ Unsupervised clustering and feature weighting based on generalized Dirichlet mixture modeling ⋮ A parameterized \(L^2\) metric between fuzzy numbers and its parameter interpretation

Uses Software

• PLCP
• SQPlab

Cites Work

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• Fuzzy sets
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