SVM kernel type

Namespace: Emgu.CV.ML.MlEnum
Assembly: Emgu.CV.ML (in Emgu.CV.ML.dll) Version: (


public enum SVM_KERNEL_TYPE
Visual Basic
Public Enumeration SVM_KERNEL_TYPE
Visual C++
public enum class SVM_KERNEL_TYPE


Member nameValueDescription
LINEAR0 No mapping is done, linear discrimination (or regression) is done in the original feature space. It is the fastest option. d(x,y) = x y == (x,y)
POLY1 polynomial kernel: d(x,y) = (gamma*(xy)+coef0)^degree
RBF2 Radial-basis-function kernel; a good choice in most cases: d(x,y) = exp(-gamma*|x-y|^2)
SIGMOID3 sigmoid function is used as a kernel: d(x,y) = tanh(gamma*(xy)+coef0)

See Also