منابع مشابه
A Robust LS-SVM Regression
In comparison to the original SVM, which involves a quadratic programming task; LS–SVM simplifies the required computation, but unfortunately the sparseness of standard SVM is lost. Another problem is that LS-SVM is only optimal if the training samples are corrupted by Gaussian noise. In Least Squares SVM (LS–SVM), the nonlinear solution is obtained, by first mapping the input vector to a high ...
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Among neural models the Support Vector Machine (SVM) solutions are attracting increasing attention, mostly because they eliminate certain crucial questions involved by neural network construction. The main drawback of standard SVM is its high computational complexity, therefore recently a new technique, the Least Squares SVM (LS–SVM) has been introduced. In this paper we present an extended vie...
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Neural networks play an important role in system modelling. This is especially true if model building is mainly based on observed data. Among neural models the Support Vector Machine (SVM) solutions are attracting increasing attention, mostly because they automatically answer certain crucial questions involved by neural network construction. They derive an ‘optimal’ network structure and answer...
متن کاملCompactly Supported RBF Kernels for Sparsifying the Gram Matrix in LS-SVM Regression Models
In this paper we investigate the use of compactly supported RBF kernels for nonlinear function estimation with LS-SVMs. The choice of compact kernels recently proposed by Genton may lead to computational improvements and memory reduction. Examples however illustrate that compactly supported RBF kernels may lead to severe loss in generalization performance for some applications, e.g. in chaotic ...
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Least Squares Support Vector Machines (LS-SVM) are the state of the art in kernel methods for regression and function approximation. In the last few years, these models have been successfully applied to time series modelling and prediction. A key issue for the good performance of a LS-SVM model are the values chosen for both the kernel parameters and its hyperparameters in order to avoid overfi...
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ژورنال
عنوان ژورنال: Journal of the Korean Data and Information Science Society
سال: 2016
ISSN: 1598-9402
DOI: 10.7465/jkdi.2016.27.3.827