Fuzzy unsupervised classification of multivariate time trajectories with the Shannon entropy regularization

DOI10.1016/j.csda.2005.01.008zbMath1445.62156OpenAlexW2064758579MaRDI QIDQ959242

Pierpaolo D'Urso, Renato Coppi

Publication date: 11 December 2008

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

Full work available at URL: https://doi.org/10.1016/j.csda.2005.01.008

zbMATH Keywords

uncertaintymaximum entropyShannon entropydynamic fuzzy clusteringentropy regularizationmultivariate time-varying data

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Statistical aspects of information-theoretic topics (62B10) Multivariate analysis and fuzziness (62H86)

Related Items (17)

Robust fuzzy clustering of multivariate time trajectories ⋮ Maximum entropy method in comminution modelling ⋮ Dense traffic flow patterns mining in bi-directional road networks using density based trajectory clustering ⋮ Fuzzy data analysis and classification. Special issue in memoriam of Professor Lotfi A. Zadeh, father of fuzzy logic ⋮ OWA-based robust fuzzy clustering of time series with typicality degrees ⋮ A Kemeny distance-based robust fuzzy clustering for preference data ⋮ Wavelets-based clustering of multivariate time series ⋮ Relative entropy fuzzy \(c\)-means clustering ⋮ Fuzzy K-medoids clustering models for fuzzy multivariate time trajectories ⋮ Robust fuzzy clustering of time series based on B-splines ⋮ Fuzzy clustering of time series in the frequency domain ⋮ GARCH-based robust clustering of time series ⋮ Robust fuzzy clustering based on quantile autocovariances ⋮ The fuzzy approach to statistical analysis ⋮ Data analysis with fuzzy clustering methods ⋮ A parameterized \(L^2\) metric between fuzzy numbers and its parameter interpretation ⋮ A fuzzy clustering model for multivariate spatial time series

Uses Software

• COOLCAT

Cites Work

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