mlpack-3.4.2/html/r2__score_8hpp_source.html

 #ifndef MLPACK_CORE_CV_METRICS_R2SCORE_HPP

 #define MLPACK_CORE_CV_METRICS_R2SCORE_HPP


 #include <mlpack/core.hpp>


 namespace mlpack {

 namespace cv {


 class R2Score

 {

  public:

   template<typename MLAlgorithm, typename DataType, typename ResponsesType>

   static double Evaluate(MLAlgorithm& model,

                          const DataType& data,

                          const ResponsesType& responses);


   static const bool NeedsMinimization = false;

 };


 } // namespace cv

 } // namespace mlpack


 // Include implementation.

 #include "r2_score_impl.hpp"


 #endif

mlpack::cv::R2Score
The R2 Score is a metric of performance for regression algorithms that represents the proportion of v...
Definition: r2_score.hpp:46

core.hpp
Include all of the base components required to write mlpack methods, and the main mlpack Doxygen docu...

mlpack::cv::R2Score::Evaluate
static double Evaluate(MLAlgorithm &model, const DataType &data, const ResponsesType &responses)
Run prediction and calculate the R squared error.

mlpack::cv::R2Score::NeedsMinimization
static const bool NeedsMinimization
Information for hyper-parameter tuning code.
Definition: r2_score.hpp:67