mlpack
r2_score.hpp
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1 
12 #ifndef MLPACK_CORE_CV_METRICS_R2SCORE_HPP
13 #define MLPACK_CORE_CV_METRICS_R2SCORE_HPP
14 
15 #include <mlpack/core.hpp>
16 
17 namespace mlpack {
18 namespace cv {
19 
46 class R2Score
47 {
48  public:
58  template<typename MLAlgorithm, typename DataType, typename ResponsesType>
59  static double Evaluate(MLAlgorithm& model,
60  const DataType& data,
61  const ResponsesType& responses);
62 
67  static const bool NeedsMinimization = false;
68 };
69 
70 } // namespace cv
71 } // namespace mlpack
72 
73 // Include implementation.
74 #include "r2_score_impl.hpp"
75 
76 #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
mlpack
Linear algebra utility functions, generally performed on matrices or vectors.
Definition: add_to_cli11.hpp:21
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