The stopping condition for the svr_linear_trainer was too tight when

there were a lot of samples, causing it to take an excessive amount
of time to converge in some cases.  This fixes it.

dlib/svm/svr_linear_trainer.h

@@ -72,6 +72,8 @@ namespace dlib
             unsigned long num_iterations
         ) const 
         {
+            current_risk_value /= samples.size();
+            current_risk_gap /= samples.size();
             if (be_verbose)
             {
                 using namespace std;

dlib/test/svr_linear_trainer.cpp

@@ -65,6 +65,7 @@ namespace
             samples[i] = ekm.project(samples[i]);
 
         svr_linear_trainer<linear_kernel<sample_type> > linear_trainer;
+        linear_trainer.set_epsilon(0.0001);
         linear_trainer.set_c(30);
         linear_trainer.set_epsilon_insensitivity(0.001);