Added get_kernel() member functions to the reduced set trainers.

Also added missing comments to the spec.

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%402424

dlib/svm/reduced.h

@@ -46,6 +46,12 @@ namespace dlib
             );
         }
 
+        const kernel_type& get_kernel (
+        ) const
+        {
+            return trainer.get_kernel();
+        }
+
         template <
             typename in_sample_vector_type,
             typename in_scalar_vector_type
@@ -187,7 +193,7 @@ namespace dlib
             COMPILE_TIME_ASSERT(is_matrix<sample_type>::value);
 
             // make sure requires clause is not broken
-            DLIB_ASSERT(num_sv > 0,
+            DLIB_ASSERT(num_sv > 0 && eps > 0,
                         "\t reduced_decision_function_trainer2()"
                         << "\n\t you have given invalid arguments to this function"
                         << "\n\t num_sv: " << num_sv 
@@ -195,6 +201,12 @@ namespace dlib
             );
         }
 
+        const kernel_type& get_kernel (
+        ) const
+        {
+            return trainer.get_kernel();
+        }
+
         template <
             typename in_sample_vector_type,
             typename in_scalar_vector_type
@@ -576,7 +588,7 @@ namespace dlib
         COMPILE_TIME_ASSERT(is_matrix<typename trainer_type::sample_type>::value);
 
         // make sure requires clause is not broken
-        DLIB_ASSERT(num_sv > 0,
+        DLIB_ASSERT(num_sv > 0 && eps > 0,
                     "\tconst reduced_decision_function_trainer2 reduced2()"
                     << "\n\t you have given invalid arguments to this function"
                     << "\n\t num_sv: " << num_sv 

dlib/svm/reduced_abstract.h

@@ -54,6 +54,14 @@ namespace dlib
                   decision_function objects with fewer support vectors.
                 - The reduced decision functions that are output will have at most
                   num_sv support vectors.
+                - #get_kernel() == trainer.get_kernel()
+        !*/
+
+        const kernel_type& get_kernel (
+        ) const;
+        /*!
+            ensures
+                - returns the kernel used by this trainer object
         !*/
 
         template <
@@ -140,12 +148,24 @@ namespace dlib
         /*!
             requires
                 - num_sv > 0
+                - eps > 0
             ensures
                 - returns a trainer object that applies post processing to the decision_function
                   objects created by the given trainer object with the goal of creating
                   decision_function objects with fewer support vectors.
                 - The reduced decision functions that are output will have at most
                   num_sv support vectors.
+                - the gradient based optimization will continue until the change in the
+                  objective function is less than eps.  So smaller values of eps will
+                  give better results but take longer to compute.
+                - #get_kernel() == trainer.get_kernel()
+        !*/
+
+        const kernel_type& get_kernel (
+        ) const;
+        /*!
+            ensures
+                - returns the kernel used by this trainer object
         !*/
 
         template <
@@ -184,6 +204,7 @@ namespace dlib
             - trainer_type == some kind of trainer object that creates decision_function
               objects (e.g. svm_nu_trainer)
             - kernel_derivative<trainer_type::kernel_type> is defined
+            - eps > 0
         ensures
             - returns a reduced_decision_function_trainer2 object that has been
               instantiated with the given arguments.