ENH: Remove useless parameters for opencv svm classification in...

ENH: Remove useless parameters for opencv svm classification in otbTrainMachineLearningImagesClassifier application.

Applications/Classification/otbTrainMachineLearningImagesClassifier.cxx

@@ -213,8 +213,8 @@ private:
        AddChoice("classifier.svm.m.csvc", "C support vector classification");
        AddChoice("classifier.svm.m.nusvc", "Nu support vector classification");
        AddChoice("classifier.svm.m.oneclass", "Distribution estimation (One Class SVM)");
-       AddChoice("classifier.svm.m.epssvr", "Epsilon Support Vector Regression");
-       AddChoice("classifier.svm.m.nusvr", "Nu Support Vector Regression");
+	//AddChoice("classifier.svm.m.epssvr", "Epsilon Support Vector Regression");
+	//AddChoice("classifier.svm.m.nusvr", "Nu Support Vector Regression");
        SetParameterString("classifier.svm.m", "csvc");
        SetParameterDescription("classifier.svm.m", "Type of SVM formulation.");
        AddParameter(ParameterType_Choice, "classifier.svm.k", "SVM Kernel Type");
@@ -230,9 +230,9 @@ private:
        AddParameter(ParameterType_Float, "classifier.svm.nu", "Parameter nu of a SVM optimization problem (NU_SVC / ONE_CLASS / NU_SVR).");
        SetParameterFloat("classifier.svm.nu", 0.0);
        SetParameterDescription("classifier.svm.nu", "Parameter nu of a SVM optimization problem.");
-       AddParameter(ParameterType_Float, "classifier.svm.p", "Parameter epsilon of a SVM optimization problem (EPS_SVR).");
-       SetParameterFloat("classifier.svm.p", 0.0);
-       SetParameterDescription("classifier.svm.p", "Parameter epsilon of a SVM optimization problem (EPS_SVR).");
+	//AddParameter(ParameterType_Float, "classifier.svm.p", "Parameter epsilon of a SVM optimization problem (EPS_SVR).");
+	//SetParameterFloat("classifier.svm.p", 0.0);
+	//SetParameterDescription("classifier.svm.p", "Parameter epsilon of a SVM optimization problem (EPS_SVR).");
        AddParameter(ParameterType_Float, "classifier.svm.coef0", "Parameter coef0 of a kernel function (POLY / SIGMOID).");
        SetParameterFloat("classifier.svm.coef0", 0.0);
        SetParameterDescription("classifier.svm.coef0", "Parameter coef0 of a kernel function (POLY / SIGMOID).");
@@ -423,14 +423,14 @@ private:
                        SVMClassifier->SetSVMType(CvSVM::ONE_CLASS);
                        std::cout<<"CvSVM::ONE_CLASS = "<<CvSVM::ONE_CLASS<<std::endl;
                      break;
-                case 3: // EPS_SVR
+		  /*case 3: // EPS_SVR
                        SVMClassifier->SetSVMType(CvSVM::EPS_SVR);
                        std::cout<<"CvSVM::EPS_SVR = "<<CvSVM::EPS_SVR<<std::endl;
                      break;
                 case 4: // NU_SVR
                        SVMClassifier->SetSVMType(CvSVM::NU_SVR);
                        std::cout<<"CvSVM::NU_SVR = "<<CvSVM::NU_SVR<<std::endl;
-                     break;
+			break;*/
                 default: // DEFAULT = C_SVC
                        SVMClassifier->SetSVMType(CvSVM::C_SVC);
                        std::cout<<"CvSVM::C_SVC = "<<CvSVM::C_SVC<<std::endl;
@@ -438,7 +438,7 @@ private:
          }
          SVMClassifier->SetC(GetParameterFloat("classifier.svm.c"));
          SVMClassifier->SetNu(GetParameterFloat("classifier.svm.nu"));
-         SVMClassifier->SetP(GetParameterFloat("classifier.svm.p"));
+         //SVMClassifier->SetP(GetParameterFloat("classifier.svm.p"));
          SVMClassifier->SetCoef0(GetParameterFloat("classifier.svm.coef0"));
          SVMClassifier->SetGamma(GetParameterFloat("classifier.svm.gamma"));
          SVMClassifier->SetDegree(GetParameterFloat("classifier.svm.degree"));