Ridge estimation for regression models with crisp inputs and Gaussian fuzzy output.

DOI10.1016/S0165-0114(03)00002-2zbMath1041.62054OpenAlexW1972017701MaRDI QIDQ1430897

Dug Hun Hong, Chulhwan Ahn, Changha Hwang

Publication date: 27 May 2004

Published in: Fuzzy Sets and Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0165-0114(03)00002-2

zbMATH Keywords

fuzzy regressionfuzzy inference systemsfuzzy system modelsridge estimation

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) General nonlinear regression (62J02)

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Cites Work

• Fuzzy least squares
• On a class of fuzzy \(c\)-numbers clustering procedures for fuzzy data
• Extended fuzzy linear models and least squares estimates
• Multi-objective fuzzy regression: A general framework
• Theoretical foundations of the potential function method in pattern recognition learning
• Linear Regression Analysis with Fuzzy Model
• Fuzzy sets
• Multidimensional least-squares fitting with a fuzzy model
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