diff --git a/Modules/Applications/AppClassification/include/otbVectorPrediction.h b/Modules/Applications/AppClassification/include/otbVectorPrediction.h
index 89f257f46bcc167897aece2a6e860b856825c0ae..7390c407f8ebda6bd9f55fce5cc9b0b6b4e928fa 100644
--- a/Modules/Applications/AppClassification/include/otbVectorPrediction.h
+++ b/Modules/Applications/AppClassification/include/otbVectorPrediction.h
@@ -98,7 +98,7 @@ private:
   /** Method returning whether the confidence map should be computed, depending on the regression mode and input parameters */
   bool shouldComputeConfidenceMap() const;
 
-  /** Method returning the input list sample from the input layer */
+  /** Method returning the input list sample from the input DataSource */
   typename ListSampleType::Pointer ReadInputListSample(ogr::DataSource::Pointer source);
 
   /** Normalize a list sample using the statistic file given  */
diff --git a/Modules/Applications/AppClassification/include/otbVectorPrediction.hxx b/Modules/Applications/AppClassification/include/otbVectorPrediction.hxx
index f62f08982ca035dc087581f2132329cd570e7593..0cc24a8befd8cc0855262c22a0e9ea9e002d1208 100644
--- a/Modules/Applications/AppClassification/include/otbVectorPrediction.hxx
+++ b/Modules/Applications/AppClassification/include/otbVectorPrediction.hxx
@@ -78,7 +78,7 @@ typename VectorPrediction<RegressionMode>::ListSampleType::Pointer VectorPredict
   auto layer  = source->GetLayer(0);
   typename ListSampleType::Pointer input = ListSampleType::New();
 
-  const unsigned int nbFeatures = GetSelectedItems("feat").size();
+  const auto nbFeatures = GetSelectedItems("feat").size();
   input->SetMeasurementVectorSize(nbFeatures);
 
   ogr::Feature             feature = layer.ogr().GetNextFeature();