Merge pull request #1430 from xtelinco/master

Return the final objective of the trained model

src/mlpack/methods/logistic_regression/logistic_regression.hpp

@@ -125,9 +125,10 @@ class LogisticRegression
    * @tparam OptimizerType Type of optimizer to use to train the model.
    * @param predictors Input training variables.
    * @param responses Outputs results from input training variables.
+   * @return The final objective of the trained model (NaN or Inf on error)
    */
   template<typename OptimizerType = mlpack::optimization::L_BFGS>
-  void Train(const MatType& predictors,
+  double Train(const MatType& predictors,
              const arma::Row<size_t>& responses);
 
   /**
@@ -145,9 +146,10 @@ class LogisticRegression
    * @param predictors Input training variables.
    * @param responses Outputs results from input training variables.
    * @param optimizer Instantiated optimizer with instantiated error function.
+   * @return The final objective of the trained model (NaN or Inf on error)
    */
   template<typename OptimizerType>
-  void Train(const MatType& predictors,
+  double Train(const MatType& predictors,
              const arma::Row<size_t>& responses,
              OptimizerType& optimizer);
 

src/mlpack/methods/logistic_regression/logistic_regression_impl.hpp

@@ -68,16 +68,16 @@ LogisticRegression<MatType>::LogisticRegression(
 
 template<typename MatType>
 template<typename OptimizerType>
-void LogisticRegression<MatType>::Train(const MatType& predictors,
+double LogisticRegression<MatType>::Train(const MatType& predictors,
                                         const arma::Row<size_t>& responses)
 {
   OptimizerType optimizer;
-  Train(predictors, responses, optimizer);
+  return Train(predictors, responses, optimizer);
 }
 
 template<typename MatType>
 template<typename OptimizerType>
-void LogisticRegression<MatType>::Train(
+double LogisticRegression<MatType>::Train(
     const MatType& predictors,
     const arma::Row<size_t>& responses,
     OptimizerType& optimizer)
@@ -93,6 +93,8 @@ void LogisticRegression<MatType>::Train(
 
   Log::Info << "LogisticRegression::LogisticRegression(): final objective of "
       << "trained model is " << out << "." << std::endl;
+
+  return out;
 }
 
 template<typename MatType>