New modifications and applications of fuzzy \(C\)-means methodology

DOI10.1016/j.csda.2007.10.020zbMath1452.62432OpenAlexW1980498000MaRDI QIDQ1023570

Bjørn-Helge Mevik, Tormod Næs, Ingunn Berget

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.10.020

zbMATH Keywords

nonlinear regressionfuzzy clusteringmixture modelsFCMnoise clusteringprediction sortingsequential clustering

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Multivariate analysis and fuzziness (62H86)

Related Items (5)

Optimal combination of aircraft maintenance tasks by a novel simplex optimization method ⋮ Fuzzy C-means clustering based on dual expression between cluster prototypes and reconstructed data ⋮ CECM: constrained evidential \(C\)-means algorithm ⋮ A NOTE ON WEIGHTED FUZZY K-MEANS CLUSTERING FOR CONCEPT DECOMPOSITION ⋮ Dealing with distances and transformations for fuzzy \(c\)-means clustering of compositional data

Uses Software

• Silhouettes

Cites Work

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• Assessing the performance of classifiers when classes arise from a continuum
• Data analysis with fuzzy clustering methods
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
• Fuzzy clustering using scatter matrices
• Detection and Characterization of Cluster Substructure I. Linear Structure: Fuzzy c-Lines
• Detection and Characterization of Cluster Substructure II. Fuzzy c-Varieties and Convex Combinations Thereof
• Multiple response surface methods in computer simulation
• Normal Discrimination with Unclassified Observations
• On clustering validation techniques

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