Fuzzy ridge regression with fuzzy input and output
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Publication:780161
DOI10.1007/s00500-019-04164-3zbMath1436.62343OpenAlexW2963810891WikidataQ127453017 ScholiaQ127453017MaRDI QIDQ780161
Mohammad Reza Rabiei, Masoumeh Farrokhi, Mohammad Arashi
Publication date: 15 July 2020
Published in: Soft Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00500-019-04164-3
Ridge regression; shrinkage estimators (Lasso) (62J07) Fuzziness, and linear inference and regression (62J86)
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Cites Work
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- Fuzzy least squares
- Possibilistic linear regression analysis for fuzzy data
- Least squares estimation of a linear regression model with LR fuzzy response
- Fuzzy data analysis by possibilistic linear models
- Possibilistic linear systems and their application to the linear regression model
- Fuzzy sets and systems. Theory and applications
- Support vector fuzzy regression machines
- Ridge estimation for regression models with crisp inputs and Gaussian fuzzy output.
- A simple method for computation of fuzzy linear regression
- Properties of certain fuzzy linear regression methods
- Asymptotic properties of least squares estimation with fuzzy observations
- Fuzzy linear regression model based on fuzzy scalar product
- A Simulation Study of Some Ridge Estimators
- Linear Regression Analysis with Fuzzy Model
- A Monte Carlo Evaluation of Some Ridge-Type Estimators
- A fuzzy robust regression approach applied to bedload transport data
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
- Multidimensional least-squares fitting with a fuzzy model
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