ENH: Added Doxygen docs for GD class and its constructor

src/LearningMethods/GradientDescent.h

@@ -19,17 +19,23 @@ namespace lib4neuro {
     private:
 
         /**
-         *
+         * Threshold for the successful ending of the optimization - deviation from minima
          */
         double tolerance;
 
         /**
-         *
+         * Number of iterations to reset step size to tolerance/10.0
          */
         size_t restart_frequency;
 
+        /**
+         * Maximal number of iterations - optimization will stop after that, even if not converged
+         */
         long long int maximum_niters;
 
+        /**
+         * Vector of minima coordinates
+         */
         std::vector<double> *optimal_parameters;
 
         /**
@@ -50,13 +56,15 @@ namespace lib4neuro {
     public:
 
         /**
-         *
-         * @param epsilon
+         * Creates an instance of Gradient Descent Optimizer (i.e. back-propagation)
+         * @param epsilon Threshold for the successful ending of the optimization - deviation from minima
+         * @param n_to_restart Number of iterations to reset step size to tolerance/10.0
+         * @param max_iters Maximal number of iterations - optimization will stop after that, even if not converged
          */
         LIB4NEURO_API GradientDescent(double epsilon = 1e-3, size_t n_to_restart = 100, long long int max_iters = -1);
 
         /**
-         *
+         * Deallocates the instance
          */
         LIB4NEURO_API ~GradientDescent();