A review and proposal of (fuzzy) clustering for nonlinearly separable data

DOI10.1016/j.ijar.2019.09.004zbMath1471.62566OpenAlexW2972365946MaRDI QIDQ2302802

Maria Brigida Ferraro, Paolo E. Giordani

Publication date: 26 February 2020

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2019.09.004

zbMATH Keywords

density-based clusteringkernel-based clusteringgraph-based clusteringfuzzy approach to clusteringmanifold-based clusteringnonlinearly separable data

Mathematics Subject Classification ID

Statistics on manifolds (62R30) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Multivariate analysis and fuzziness (62H86)

Related Items (1)

Special issue on 9th international conference on soft methods in probability and statistics (SMPS)

Uses Software

• R
• UCI-ml
• vegan
• fpc
• Kernlab
• dbscan
• fclust
• fc
• clusfind
• Algorithm 97
• Isomap

Cites Work

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• A note on two problems in connexion with graphs
• Graph clustering
• Generalised kernel weighted fuzzy c-means clustering algorithm with local information
• Fuzzy extensions of the DBSCAN clustering algorithm
• A fuzzy clustering procedure for random fuzzy sets
• Robustness of density-based clustering methods with various neighborhood relations
• Modern multidimensional scaling. Theory and applications.
• Fuzzy clustering for the estimation of the parameters of the components of mixtures of normal distributions
• Finding Groups in Data
• Geodesic Distance Based Fuzzy Clustering
• Nonlinear Dimensionality Reduction
• Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters
• A Theorem on Boolean Matrices
• Approaches for scaling DBSCAN algorithm to large spatial databases

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