Aakash-kaushik/mlpack/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 {

 template<bool AdjustedR2>
 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:51

data

mlpack
Linear algebra utility functions, generally performed on matrices or vectors.
Definition: cv.hpp:1

mlpack::cv::R2Score::Evaluate
static double Evaluate(MLAlgorithm &model, const DataType &data, const ResponsesType &responses)
Run prediction and calculate the R squared or Adjusted R squared error.
Definition: r2_score_impl.hpp:20

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

mlpack::cv::R2Score::NeedsMinimization
static const bool NeedsMinimization
Information for hyper-parameter tuning code.
Definition: r2_score.hpp:72

r2_score_impl.hpp