p, nu and coef0 parameters does not change during SVM::trainAuto training
Hello,
The values of p, nu and coef0 parameters are not getting updated in SVM::trainAuto training. It is always zero. The parameters gamma and cvalue are getting changed. Is this normal? Are the best values of these parameters usually zero?
The kernel type used is RBF and svm type is C_SVC
Also is there any way we can improve a two class classification other than making the parameter balanced = true in SVM::trainAuto training.
The project is forgery detection where we have to distinguish between forged and pristine images.
can you show, how you call it ?
(also, just curious: "distinguish between forged and pristine images." -- images of what ?)
//Set up SVM's parameters CvSVMParams params; params.svm_type = CvSVM::C_SVC; params.kernel_type = CvSVM::RBF; params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 500, 1e-6); params.gamma = .01; params.C = 12; params.coef0 = 3; params.nu = .1; params.p = 3;
This is on opencv 2.45, but was tested on opencv 3.1 on friends machine using trainAuto. Results are same.
Any image will do. The original is considered to be pristine. Any tampering like splicing is performed on this image. The resultant image is a forged image.Usually the image size is 1024x768 rgbimage.
Thanks for the answer.
Regards Amal