SMKFC-ER: semi-supervised multiple kernel fuzzy clustering based on entropy and relative entropy

DOI10.1016/J.INS.2020.08.094zbMath1479.62051OpenAlexW3081852103MaRDI QIDQ2056326

Mohammad Reza Keyvanpour, Fariba Salehi, Arash Sharifi

Publication date: 2 December 2021

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

Full work available at URL: https://doi.org/10.1016/j.ins.2020.08.094

zbMATH Keywords

entropyrelative entropymultiple kernelknowledge-based fuzzy clusteringsemi-supervised fuzzy clusteringunsupervised fuzzy clustering

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Multivariate analysis and fuzziness (62H86) Statistical aspects of fuzziness, sufficiency, and information (62B86)

Related Items (3)

Multi-objective soft subspace clustering in the composite kernel space ⋮ Entropy measure for orderable sets ⋮ Adaptive explicit kernel Minkowski weighted K-means

Uses Software

• UCI-ml

Cites Work

• Unnamed Item
• A new credibilistic clustering algorithm
• Fuzzy granular gravitational clustering algorithm for multivariate data
• Interval type-2 relative entropy fuzzy C-means clustering
• Relative entropy fuzzy \(c\)-means clustering
• Gaussian clustering method based on maximum-fuzzy-entropy interpretation
• Relative entropy collaborative fuzzy clustering method
• Enhancement of fuzzy clustering by mechanisms of partial supervision
• Collaborative fuzzy clustering
• Knowledge‐Based Clustering
• A discrete-valued clustering algorithm with applications to biomolecular data

This page was built for publication: SMKFC-ER: semi-supervised multiple kernel fuzzy clustering based on entropy and relative entropy