From 316cd8e0c85ba0300d4807ba0bd68aca39293ac6 Mon Sep 17 00:00:00 2001
From: Antoine Regimbeau <antoine.regimbeau@c-s.fr>
Date: Fri, 21 Jul 2017 11:02:08 +0200
Subject: [PATCH] Bug fixed. We might want to check the behavior of the nu
 classification as there is a lot of value that are not acceptable. Either it
 is the model then it's okay or it's a method that does a strange manipulation
 changing its value.

---
 .../include/otbTrainLibSVM.txx                | 23 +++++++++++++------
 .../include/otbLibSVMMachineLearningModel.h   |  2 +-
 2 files changed, 17 insertions(+), 8 deletions(-)

diff --git a/Modules/Applications/AppClassification/include/otbTrainLibSVM.txx b/Modules/Applications/AppClassification/include/otbTrainLibSVM.txx
index c380f56de1..82d5bd8410 100644
--- a/Modules/Applications/AppClassification/include/otbTrainLibSVM.txx
+++ b/Modules/Applications/AppClassification/include/otbTrainLibSVM.txx
@@ -97,6 +97,12 @@ namespace Wrapper
     SetParameterDescription("classifier.libsvm.c",
         "SVM models have a cost parameter C (1 by default) to control the "
         "trade-off between training errors and forcing rigid margins.");
+
+    AddParameter(ParameterType_Float, "classifier.libsvm.nu", "Cost parameter Nu");
+    SetParameterFloat("classifier.libsvm.nu",0.5, false);
+    SetParameterDescription("classifier.libsvm.nu",
+        "Cost parameter Nu, in the range 0..1, the larger the value, "
+        "the smoother the decision.");
     
     // It seems that it miss a nu parameter for the nu-SVM use. 
     AddParameter(ParameterType_Empty, "classifier.libsvm.opt", "Parameters optimization");
@@ -111,12 +117,14 @@ namespace Wrapper
       AddParameter(ParameterType_Float, "classifier.libsvm.eps", "Epsilon");
       SetParameterFloat("classifier.libsvm.eps",1e-3, false);
       SetParameterDescription("classifier.libsvm.eps", 
-        "Parameter for the epsilon regression mode.");
-      AddParameter(ParameterType_Float, "classifier.libsvm.nu", "Nu");
-      SetParameterFloat("classifier.libsvm.nu",0.5, false);
-      SetParameterDescription("classifier.libsvm.nu", 
-        "Cost parameter Nu, in the range 0..1, the larger the value, "
-        "the smoother the decision.");
+        "The distance between feature vectors from the training set and "
+        "the fitting hyper-plane must be less than Epsilon. For outliers"
+        "the penalty mutliplier is set by C.");
+      // AddParameter(ParameterType_Float, "classifier.libsvm.nu", "Nu");
+      // SetParameterFloat("classifier.libsvm.nu",0.5, false);
+      // SetParameterDescription("classifier.libsvm.nu", 
+      //   "Cost parameter Nu, in the range 0..1, the larger the value, "
+      //   "the smoother the decision.");
       }
   }
 
@@ -142,6 +150,7 @@ namespace Wrapper
       {
       libSVMClassifier->SetDoProbabilityEstimates(true);
       }
+    libSVMClassifier->SetNu(GetParameterFloat("classifier.libsvm.nu"));
     libSVMClassifier->SetC(GetParameterFloat("classifier.libsvm.c"));
 
     switch (GetParameterInt("classifier.libsvm.k"))
@@ -177,7 +186,6 @@ namespace Wrapper
           break;
         }
       libSVMClassifier->SetEpsilon(GetParameterFloat("classifier.libsvm.eps"));
-      libSVMClassifier->SetNu(GetParameterFloat("classifier.libsvm.nu"));
       }
     else
       {
@@ -197,6 +205,7 @@ namespace Wrapper
           break;
         }
       }
+      
 
     libSVMClassifier->Train();
     libSVMClassifier->Save(modelPath);
diff --git a/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.h b/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.h
index a8baa08e58..329722af5a 100644
--- a/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.h
@@ -141,7 +141,7 @@ public:
     return m_Parameters.coef0;
   }
 
-  /** Set the C parameter for the training for C_SVC, EPSILON_SVR and NU_SVR */
+  /** Set the C parameter for the training for C_SVC, EPSILON_SVR and C_SVR */
   otbSetSVMParameterMacro(C,C,double)
 
   /** Get the C parameter for the training for C_SVC, EPSILON_SVR and NU_SVR */
-- 
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