Support vector interval regression networks for interval regression analysis.

DOI10.1016/S0165-0114(02)00570-5zbMath1043.62064OpenAlexW2083480853MaRDI QIDQ1406871

Shun-Feng Su, Chen-Chia Chuang, Jin-Tsong Jeng

Publication date: 7 September 2003

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

Full work available at URL: https://doi.org/10.1016/s0165-0114(02)00570-5

zbMATH Keywords

OutliersInterval regression analysisSupport vector interval regression networks

Mathematics Subject Classification ID

Linear inference, regression (62J99) Applications of mathematical programming (90C90) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items

A \(\nu \)-twin support vector machine (\(\nu \)-TSVM) classifier and its geometric algorithms ⋮ A parametric recurrent neural network scheme for solving a class of fuzzy regression models with some real-world applications ⋮ The normalized interval regression model with outlier detection and its real-world application to house pricing problems ⋮ Regression analysis of belief functions on interval-valued variables: comparative studies ⋮ Interval regression by tolerance analysis approach ⋮ Conservative and aggressive rough SVR modeling ⋮ A reduced support vector machine approach for interval regression analysis ⋮ Extended support vector interval regression networks for interval input-output data ⋮ An understandable way to discover methods to model interval input-output samples ⋮ Rough support vector regression ⋮ On support vector regression machines with linguistic interpretation of the kernel matrix ⋮ Support vector interval regression machine for crisp input and output data ⋮ New support vector algorithms with parametric insensitive/margin model ⋮ Applying nonlinear generalized autoregressive conditional heteroscedasticity to compensate ANFIS outputs tuned by adaptive support vector regression ⋮ CCH-based geometric algorithms for SVM and applications ⋮ Parameter estimation from interval-valued data using the expectation-maximization algorithm ⋮ Asymmetrical interval regression using extended \(\epsilon \)-SVM with robust algorithm ⋮ Interval regression analysis using support vector networks

Cites Work

• Fuzzy linear regression and its applications to forecasting in uncertain environment
• An architecture of neural networks with interval weights and its application to fuzzy regression analysis
• Robust Statistics
• Fuzzy regression using asymmetric fuzzy coefficients and fuzzified neural networks
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item