我想优化Opencv中的SVM参数。但是,每次我使用train_auto
I get C=1
and gamma=1
。有些人使用 LibSVM,但我无法为此编写包装器。两个都trainingData
and labels
取自现有代码,该代码给出了良好的结果,因此我尝试使用该代码获取相同的参数train_auto
。在原来的代码中C=312.5
and gamma=0.50625
。我看到有人用过CvStatModel
对于python,C++有必要吗?我哪里出错了?
提前致谢。
代码:
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;