diff --git a/Documentation/Cookbook/rst/recipes/pbclassif.rst b/Documentation/Cookbook/rst/recipes/pbclassif.rst
index 5ff4d7764344ea6966268ce3162461c07746af4d..dbeeadd8abb8b9b775db2ffb3f65b834fbdea7b0 100644
--- a/Documentation/Cookbook/rst/recipes/pbclassif.rst
+++ b/Documentation/Cookbook/rst/recipes/pbclassif.rst
@@ -895,7 +895,7 @@ Two applications are available for training:
 
 
 - `TrainImagesRegression` can be used to train a classifier from multiple pairs of predictor images and label images. 
-  There is two ways to use this application:
+  There are two ways to use this application:
 
   It is possible to provide for each input image a vector data file with geometries
   corresponding to the input locations that will be used for training. This is achieved by using the `io.vd` parameter.
diff --git a/Modules/Applications/AppClassification/app/otbImageRegression.cxx b/Modules/Applications/AppClassification/app/otbImageRegression.cxx
index f1892417da6d1e853d3cb6412f890d8c7ec7ade6..15f4e7b4d0c664b0bb6a054e76184d690fdf5308 100644
--- a/Modules/Applications/AppClassification/app/otbImageRegression.cxx
+++ b/Modules/Applications/AppClassification/app/otbImageRegression.cxx
@@ -44,16 +44,6 @@ class AffineFunctor
 public:
   typedef double InternalType;
 
-  // constructor
-  AffineFunctor() : m_A(1.0), m_B(0.0)
-  {
-  }
-
-  // destructor
-  virtual ~AffineFunctor()
-  {
-  }
-
   void SetA(InternalType a)
   {
     m_A = a;
@@ -70,8 +60,8 @@ public:
   }
 
 private:
-  InternalType m_A;
-  InternalType m_B;
+  InternalType m_A = 1.0;
+  InternalType m_B = 0.0;
 };
 }