Aggregation invariance in general clustering approaches

DOI10.1007/s11634-009-0052-9zbMath1306.62137OpenAlexW2010797828MaRDI QIDQ481908

François Bavaud

Publication date: 18 December 2014

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: https://serval.unil.ch/resource/serval:BIB_E83647B5E790.P001/REF.pdf

zbMATH Keywords

EM algorithmmutual informationmodel-based clusteringfuzzy clustering\(c\)-means clusteringaggregation invariance

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Phase transitions (general) in equilibrium statistical mechanics (82B26) Measures of information, entropy (94A17) Fuzzy sets and logic (in connection with information, communication, or circuits theory) (94D05) Multivariate analysis and fuzziness (62H86)

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Cites Work

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• Algorithms for fuzzy clustering. Methods in \(c\)-means clustering with applications
• A classification EM algorithm for clustering and two stochastic versions
• Remarks to Maurice Frechet's article ``Sur la definition axiomatique d'une classe d'espaces vectoriels distancies applicables vectoriellement sur l'espace de Hilbert
• Quantization