Added missing get/set epsilon functions to the RVM training objects.

I also changed the default epsilon from 0.0005 to 0.001.

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403777

dlib/svm/rvm.h

@@ -147,10 +147,29 @@ namespace dlib
         typedef decision_function<kernel_type> trained_function_type;
 
         rvm_trainer (
-        ) : eps(0.0005)
+        ) : eps(0.001)
         {
         }
 
+        void set_epsilon (
+            scalar_type eps_
+        )
+        {
+            // make sure requires clause is not broken
+            DLIB_ASSERT(eps_ > 0,
+                "\tvoid rvm_trainer::set_epsilon(eps_)"
+                << "\n\t invalid inputs were given to this function"
+                << "\n\t eps: " << eps_ 
+                );
+            eps = eps_;
+        }
+
+        const scalar_type get_epsilon (
+        ) const
+        { 
+            return eps;
+        }
+
         void set_kernel (
             const kernel_type& k
         )
@@ -600,8 +619,27 @@ namespace dlib
         typedef decision_function<kernel_type> trained_function_type;
 
         rvm_regression_trainer (
-        ) : eps(0.0005)
+        ) : eps(0.001)
+        {
+        }
+
+        void set_epsilon (
+            scalar_type eps_
+        )
+        {
+            // make sure requires clause is not broken
+            DLIB_ASSERT(eps_ > 0,
+                "\tvoid rvm_regression_trainer::set_epsilon(eps_)"
+                << "\n\t invalid inputs were given to this function"
+                << "\n\t eps: " << eps_ 
+                );
+            eps = eps_;
+        }
+
+        const scalar_type get_epsilon (
+        ) const
         { 
+            return eps;
         }
 
         void set_kernel (

dlib/svm/rvm_abstract.h

@@ -49,6 +49,26 @@ namespace dlib
             ensures
                 - This object is properly initialized and ready to be used
                   to train a relevance vector machine.
+                - #get_epsilon() == 0.001
+        !*/
+
+        void set_epsilon (
+            scalar_type eps
+        );
+        /*!
+            requires
+                - eps > 0
+            ensures
+                - #get_epsilon() == eps 
+        !*/
+
+        const scalar_type get_epsilon (
+        ) const;
+        /*!
+            ensures
+                - returns the error epsilon that determines when training should stop.
+                  Generally a good value for this is 0.001.  Smaller values may result
+                  in a more accurate solution but take longer to execute.
         !*/
 
         void set_kernel (
@@ -152,6 +172,26 @@ namespace dlib
             ensures
                 - This object is properly initialized and ready to be used
                   to train a relevance vector machine.
+                - #get_epsilon() == 0.001
+        !*/
+
+        void set_epsilon (
+            scalar_type eps
+        );
+        /*!
+            requires
+                - eps > 0
+            ensures
+                - #get_epsilon() == eps 
+        !*/
+
+        const scalar_type get_epsilon (
+        ) const;
+        /*!
+            ensures
+                - returns the error epsilon that determines when training should stop.
+                  Generally a good value for this is 0.001.  Smaller values may result
+                  in a more accurate solution but take longer to execute.
         !*/
 
         void set_kernel (