ENH: report regression flag to machine learning model

Modules/Applications/AppClassification/include/otbLearningApplicationBase.txx

@@ -74,6 +74,7 @@ LearningApplicationBase<TInputValue,TOutputValue>
     }
 
   model->Load(modelPath);
+  model->SetRegressionMode(this->m_RegressionFlag);
   model->SetInputListSample(validationListSample);
   model->SetTargetListSample(predictedList);
   model->PredictAll();

Modules/Applications/AppClassification/include/otbTrainBoost.txx

@@ -66,6 +66,7 @@ namespace Wrapper
                std::string modelPath)
   {
     typename BoostType::Pointer boostClassifier = BoostType::New();
+    boostClassifier->SetRegressionMode(this->m_RegressionFlag);
     boostClassifier->SetInputListSample(trainingListSample);
     boostClassifier->SetTargetListSample(trainingLabeledListSample);
     boostClassifier->SetBoostType(GetParameterInt("classifier.boost.t"));

Modules/Applications/AppClassification/include/otbTrainDecisionTree.txx

@@ -93,6 +93,7 @@ LearningApplicationBase<TInputValue,TOutputValue>
                     std::string modelPath)
 {
   typename DecisionTreeType::Pointer classifier = DecisionTreeType::New();
+  classifier->SetRegressionMode(this->m_RegressionFlag);
   classifier->SetInputListSample(trainingListSample);
   classifier->SetTargetListSample(trainingLabeledListSample);
   classifier->SetMaxDepth(GetParameterInt("classifier.dt.max"));

Modules/Applications/AppClassification/include/otbTrainGradientBoostedTree.txx

@@ -79,6 +79,7 @@ LearningApplicationBase<TInputValue,TOutputValue>
                            std::string modelPath)
 {
   typename GradientBoostedTreeType::Pointer classifier = GradientBoostedTreeType::New();
+  classifier->SetRegressionMode(this->m_RegressionFlag);
   classifier->SetInputListSample(trainingListSample);
   classifier->SetTargetListSample(trainingLabeledListSample);
   classifier->SetWeakCount(GetParameterInt("classifier.gbt.w"));

Modules/Applications/AppClassification/include/otbTrainKNN.txx

@@ -47,6 +47,7 @@ namespace Wrapper
              std::string modelPath)
   {
     typename KNNType::Pointer knnClassifier = KNNType::New();
+    knnClassifier->SetRegressionMode(this->m_RegressionFlag);
     knnClassifier->SetInputListSample(trainingListSample);
     knnClassifier->SetTargetListSample(trainingLabeledListSample);
     knnClassifier->SetK(GetParameterInt("classifier.knn.k"));

Modules/Applications/AppClassification/include/otbTrainLibSVM.txx

@@ -58,6 +58,7 @@ namespace Wrapper
                 std::string modelPath)
   {
     typename LibSVMType::Pointer libSVMClassifier = LibSVMType::New();
+    libSVMClassifier->SetRegressionMode(this->m_RegressionFlag);
     libSVMClassifier->SetInputListSample(trainingListSample);
     libSVMClassifier->SetTargetListSample(trainingLabeledListSample);
     //SVM Option

Modules/Applications/AppClassification/include/otbTrainNeuralNetwork.txx

@@ -131,6 +131,7 @@ LearningApplicationBase<TInputValue,TOutputValue>
                      std::string modelPath)
 {
   typename NeuralNetworkType::Pointer classifier = NeuralNetworkType::New();
+  classifier->SetRegressionMode(this->m_RegressionFlag);
   classifier->SetInputListSample(trainingListSample);
   classifier->SetTargetListSample(trainingLabeledListSample);
 

Modules/Applications/AppClassification/include/otbTrainNormalBayes.txx

@@ -42,6 +42,7 @@ namespace Wrapper
                      std::string modelPath)
   {
     typename NormalBayesType::Pointer classifier = NormalBayesType::New();
+    classifier->SetRegressionMode(this->m_RegressionFlag);
     classifier->SetInputListSample(trainingListSample);
     classifier->SetTargetListSample(trainingLabeledListSample);
     classifier->Train();

Modules/Applications/AppClassification/include/otbTrainRandomForests.txx

@@ -107,6 +107,7 @@ LearningApplicationBase<TInputValue,TOutputValue>
                      std::string modelPath)
 {
   typename RandomForestType::Pointer classifier = RandomForestType::New();
+  classifier->SetRegressionMode(this->m_RegressionFlag);
   classifier->SetInputListSample(trainingListSample);
   classifier->SetTargetListSample(trainingLabeledListSample);
   classifier->SetMaxDepth(GetParameterInt("classifier.rf.max"));

Modules/Applications/AppClassification/include/otbTrainSVM.txx

@@ -87,6 +87,7 @@ namespace Wrapper
              std::string modelPath)
   {
     typename SVMType::Pointer SVMClassifier = SVMType::New();
+    SVMClassifier->SetRegressionMode(this->m_RegressionFlag);
     SVMClassifier->SetInputListSample(trainingListSample);
     SVMClassifier->SetTargetListSample(trainingLabeledListSample);
     switch (GetParameterInt("classifier.svm.k"))