I want to optimize SVM parameters in Opencv. But, every time I use train_auto
I get C=1
and gamma=1
. Some people use LibSVM but I could not write a wrapper for that. Both trainingData
and labels
are taken from an existing code which gives good results so I am trying to get the same parameters for that code with train_auto
. In the original code C=312.5
and gamma=0.50625
. I saw that somebody used CvStatModel
for python, is it necessary for C++? Where do I make a mistake?
Thanks in advance.
The Code:
CvParamGrid CvParamGrid_C(pow(2.0,-5), pow(2.0,15), pow(2.0,2));
CvParamGrid CvParamGrid_gamma(pow(2.0,-15), pow(2.0,3), pow(2.0,2));
if (!CvParamGrid_C.check() || !CvParamGrid_gamma.check())
cout<<"The grid is NOT VALID."<<endl;
CvSVMParams paramz;
paramz.kernel_type = CvSVM::RBF;
paramz.svm_type = CvSVM::C_SVC;
paramz.term_crit = cvTermCriteria(CV_TERMCRIT_ITER,100,0.000001);
svm.train_auto(trainingData, labels, Mat(), Mat(), paramz,10, CvParamGrid_C, CvParamGrid_gamma, CvSVM::get_default_grid(CvSVM::P), CvSVM::get_default_grid(CvSVM::NU), CvSVM::get_default_grid(CvSVM::COEF), CvSVM::get_default_grid(CvSVM::DEGREE), true);
svm.get_params();
cout<<"gamma:"<<paramz.gamma<<endl;
cout<<"C:"<<paramz.C<<endl;
I modified the code as follows paramz = svm.get_params()
and it worked fine.
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