Multidimensional splines with infinite number of knots as SVM kernels

@article{Izmailov2013MultidimensionalSW,
  title={Multidimensional splines with infinite number of knots as SVM kernels},
  author={Rauf Izmailov and Vladimir Vapnik and Akshay Vashist},
  journal={The 2013 International Joint Conference on Neural Networks (IJCNN)},
  year={2013},
  pages={1-7}
}
Radial basis function (RBF) kernels for SVM have been routinely used in a wide range of classification problems, delivering consistently good performance for those problems where the kernel computations are numerically feasible (high-dimensional problems typically use linear kernels). One of the drawbacks of RBF kernels is the necessity of selecting the proper value of the hyperparameter γ in addition to the standard SVM penalty parameter C - this process can lead to overfitting. Another (more… CONTINUE READING