Enum SVM.KernelTypes
SVM kernel type
Namespace: OpenCvSharp.ML
Assembly: OpenCvSharp.dll
Syntax
public enum KernelTypesFields
| Name | Description |
|---|---|
| Chi2 | Exponential Chi2 kernel, similar to the RBF kernel: \f$K(x_i, x_j) = e^{-\gamma \chi^2(x_i,x_j)}, \chi^2(x_i,x_j) = (x_i-x_j)^2/(x_i+x_j), \gamma > 0\f$. |
| Custom | Returned by SVM::getKernelType in case when custom kernel has been set |
| Inter | Histogram intersection kernel. A fast kernel. \f$K(x_i, x_j) = min(x_i,x_j)\f$. |
| Linear | Linear kernel. No mapping is done, linear discrimination (or regression) is done in the original feature space. It is the fastest option. \f$K(x_i, x_j) = x_i^T x_j\f$. |
| Poly | Polynomial kernel: \f$K(x_i, x_j) = (\gamma x_i^T x_j + coef0)^{degree}, \gamma > 0\f$. |
| Rbf | Radial basis function (RBF), a good choice in most cases. \f$K(x_i, x_j) = e^{-\gamma ||x_i - x_j||^2}, \gamma > 0\f$. |
| Sigmoid | Sigmoid kernel: \f$K(x_i, x_j) = \tanh(\gamma x_i^T x_j + coef0)\f$. |