Results 251 to 260 of about 869,216 (289)

Field Support Vector Regression

2017
In regression tasks for static data, existing methods often assume that they were generated from an identical and independent distribution (i.i.d.). However, violation can be found when input samples may form groups, each affected by a certain different domain.
Haochuan Jiang, Kaizhu Huang, Rui Zhang
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Support vector survival regression

4th IET International Conference on Advances in Medical, Signal and Information Processing (MEDSIP 2008), 2008
In this paper we show how the survival analysis problem can be formulated in terms of support vector regression, even in cases of censored observations. We prove bounds on the estimation error and we deduce that censoring is a limiting factor in the accuracy of solutions, although the convergence rate is of the same order as for uncensored observations.
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Extreme Support Vector Regression

2014
Extreme Support Vector Machine (ESVM), a variant of ELM, is a nonlinear SVM algorithm based on regularized least squares optimization. In this chapter, a regression algorithm, Extreme Support Vector Regression (ESVR), is proposed based on ESVM. Experiments show that, ESVR has a better generalization ability than the traditional ELM.
Wentao Zhu, Jun Miao, Laiyun Qing
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Optimisation of Support Vector Regression Parameters

NIR news, 2006
Contains fulltext : 35548.pdf (Publisher’s version ) (Closed access)
Üstün, B., Melssen, W.J., Buydens, L.M.C.   +2 more
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Hierarchical Approach for Multiscale Support Vector Regression

IEEE Transactions on Neural Networks and Learning Systems, 2012
Support vector regression (SVR) is based on a linear combination of displaced replicas of the same function, called a kernel. When the function to be approximated is nonstationary, the single kernel approach may be ineffective, as it is not able to follow the variations in the frequency content in the different regions of the input space.
F. Bellocchio, S. Ferrari, V. Piuri, N.A. Borghese   +3 more
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TWSVR: Regression via Twin Support Vector Machine

Neural Networks, 2016
Taking motivation from Twin Support Vector Machine (TWSVM) formulation, Peng (2010) attempted to propose Twin Support Vector Regression (TSVR) where the regressor is obtained via solving a pair of quadratic programming problems (QPPs). In this paper we argue that TSVR formulation is not in the true spirit of TWSVM.
Khemchandani, Reshma, Goyal, Keshav, Chandra, Suresh   +2 more
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Hierarchical Support Vector Regression

2012
In the previous chapter the RBFN model and the advantages of a hierarchical version for surface reconstruction has been presented. In a similar way in this chapter another paradigm, Support Vector Regression (SVR), and its hierarchical version, Hierarchical Support Vector Regression (HSVR) that allows an efficient construction of the approximating ...
Francesco Bellocchio, N. Alberto Borghese, Stefano Ferrari, Vincenzo Piuri   +3 more
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Support vector regression and least squares support vector regression for hormetic dose–response curves fitting

Chemosphere, 2010
Accurate description of hormetic dose-response curves (DRC) is a key step for the determination of the efficacy and hazards of the pollutants with the hormetic phenomenon. This study tries to use support vector regression (SVR) and least squares support vector regression (LS-SVR) to address the problem of curve fitting existing in hormesis. The SVR and
Li-Tang, Qin, Shu-Shen, Liu, Hai-Ling, Liu, Yong-Hong, Zhang   +3 more
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Balanced Support Vector Regression

2015
We propose a novel idea of regression - balancing the distances from a regression function to all examples. We created a method, called balanced support vector regression (balanced SVR) in which we incorporated this idea to support vector regression (SVR) by adding an equality constraint to the SVR optimization problem.
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Support vector interval regression networks for interval regression analysis

Fuzzy Sets and Systems, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jeng, Jin-Tsong, Chuang, Chen-Chia, Su, Shun-Feng   +2 more
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