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Sep 13, 2024 · Its performance is determined by parameter selection, which is usually achieved by a time-consuming grid search cross-validation procedure.
The article describes the two kinds of optimization parameters of the heuristic algorithm, they are genetic algorithm and particle swarm algorithm, heuristic ...
Its performance is determined by parameter selection, which is usually achieved by a time-consuming grid search cross-validation procedure. There exist, however ...
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In this paper a heuristic method for setting both the σ parameter of the Gaussian kernel and the regularization hyperparameter based on information extracted ...
Its performance is determined by parameter selection, which is usually achieved by a time-consuming grid search crossvalidation procedure. There exist, however, ...
In this paper a heuristic method for setting both the parameter of the Gaussian kernel and the regularization hyperparameter based on information extracted ...
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Feb 7, 2012 · Have a quick question about parameter selection for an SVM. I'm using a rbf kernel, so trying to optimize C and gamma. I have an example set of ...
A heuristic approach is proposed to tune the parameters of SVM in this paper. We firstly select sigma, and then search the optimal value of C with given sigma.
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The aim of this study is to apply and compare three heuristics, nature-inspired optimization techniques, cuckoo search optimization, ant lion optimization, and ...
Jul 21, 2006 · Appropriate selection of the free parameters for an SVM is critical for obtaining good performance. Initially, Vapnik. [22] recommended direct ...