Fixed grammar.

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403542

examples/model_selection_ex.cpp

@@ -141,7 +141,7 @@ int main()
         // Now that we have some data we want to train on it.  However, there are two parameters to the 
         // training.  These are the nu and gamma parameters.  Our choice for these parameters will 
         // influence how good the resulting decision function is.  To test how good a particular choice 
-        // of these parameters are we can use the cross_validate_trainer() function to perform n-fold cross
+        // of these parameters is we can use the cross_validate_trainer() function to perform n-fold cross
         // validation on our training data.  However, there is a problem with the way we have sampled 
         // our distribution above.  The problem is that there is a definite ordering to the samples.  
         // That is, the first half of the samples look like they are from a different distribution 

examples/rvm_ex.cpp

@@ -87,7 +87,7 @@ int main()
     // Now that we have some data we want to train on it.  However, there is a parameter to the 
     // training.  This is the gamma parameter of the RBF kernel.  Our choice for this parameter will 
     // influence how good the resulting decision function is.  To test how good a particular choice of
-    // kernel parameters are we can use the cross_validate_trainer() function to perform n-fold cross
+    // kernel parameters is we can use the cross_validate_trainer() function to perform n-fold cross
     // validation on our training data.  However, there is a problem with the way we have sampled 
     // our distribution.  The problem is that there is a definite ordering to the samples.  
     // That is, the first half of the samples look like they are from a different distribution 

examples/svm_ex.cpp

@@ -85,7 +85,7 @@ int main()
     // Now that we have some data we want to train on it.  However, there are two parameters to the 
     // training.  These are the nu and gamma parameters.  Our choice for these parameters will 
     // influence how good the resulting decision function is.  To test how good a particular choice 
-    // of these parameters are we can use the cross_validate_trainer() function to perform n-fold cross
+    // of these parameters is we can use the cross_validate_trainer() function to perform n-fold cross
     // validation on our training data.  However, there is a problem with the way we have sampled 
     // our distribution above.  The problem is that there is a definite ordering to the samples.  
     // That is, the first half of the samples look like they are from a different distribution