Sentence examples for by tuning the kernel from inspiring English sources

There are several methods for obtaining a valid and fitting kernel by tuning the kernel matrices weights (Gönen and Alpaydin, 2011).

For the purpose of classification, different models of LS-SVM were constructed while tuning the kernel parameters automatically and manually.

Similarly, the SVM with the 'rbf2' kernel also demonstrates similar diagnostic results as before, where 'rbf2' is obtained by tuning the bandwidth parameter in the original Gaussian kernel.

Most of the methods using these formulations propose to learn the combined kernels by tuning automatically the kernel weights (Gönen and Alpayd, 2011).

For the RBF kernel, we found that tuning the SMO cost parameter C and the RBF kernel parameter γ is necessary to obtain satisfactory performance.

For the RBF kernel, we found that tuning the SVM cost parameter C and the RBF kernel parameter γ were necessary and important to obtain satisfactory performances of SVM.

There are two key issues in the RKHS regression pertaining to the non-parametric term: choosing the matrix of kernels, and tuning the h and λ parameters.

Tuning parameters include the kernel function (for instance linear and radial), the cost (for both linear and radial kernels) and the parameter controlling the width of the radial kernel.

For linear kernel, we tuned the single parameter of cost C to optimize the SVM model; while for RBF kernel, we optimized both cost C and gamma using the grid tool in Libsvm.

We chose the Radial Basic Function (RBF) as the kernel function and tuned the parameters using the grid search strategy in LibSVM.

We used the Radial Basis Function kernel, and tuned the cost (c) and gamma parameters to optimize the classification performance on the training dataset.