A reduced support vector machine approach for interval regression analysis
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Publication:456448
DOI10.1016/j.ins.2012.06.030zbMath1250.68226OpenAlexW2028027179MaRDI QIDQ456448
Publication date: 25 October 2012
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2012.06.030
Related Items (8)
A fuzzy empirical quantile-based regression model based on triangular fuzzy numbers ⋮ New Hermite orthogonal polynomial kernel and combined kernels in support vector machine classifier ⋮ A fuzzy linear regression model with autoregressive fuzzy errors based on exact predictors and fuzzy responses ⋮ Dual possibilistic regression analysis using support vector networks ⋮ A set arithmetic-based linear regression model for modelling interval-valued responses through real-valued variables ⋮ A robust support vector regression with exact predictors and fuzzy responses ⋮ Incremental kernel minimum squared error (KMSE) ⋮ Fuzzy spline univariate regression with exact predictors and fuzzy responses
Uses Software
Cites Work
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- Linear and nonlinear fuzzy regression: Evolutionary algorithm solutions
- Support-vector networks
- Linear Regression Analysis with Fuzzy Model
- A Practical Approach to Nonlinear Fuzzy Regression
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