13 #ifndef MLPACK_METHODS_CF_NORMALIZATION_OVERALL_MEAN_NORMALIZATION_HPP    14 #define MLPACK_METHODS_CF_NORMALIZATION_OVERALL_MEAN_NORMALIZATION_HPP    52     mean = arma::mean(data.row(2));
    56     data.row(2).for_each([](
double& x)
    59         x = std::numeric_limits<double>::min();
    71     if (cleanedData.n_nonzero != 0)
    73       mean = arma::accu(cleanedData) / cleanedData.n_nonzero;
    75       arma::sp_mat::iterator it = cleanedData.begin();
    76       arma::sp_mat::iterator it_end = cleanedData.end();
    77       for (; it != it_end; ++it)
    79         double tmp = *it - mean;
    84           tmp = std::numeric_limits<float>::min();
   105                      const double rating)
 const   107     return rating + mean;
   117                    arma::vec& predictions)
 const   133   template<
typename Archive>
   136     ar(CEREAL_NVP(mean));
 OverallMeanNormalization()
 
double Denormalize(const size_t, const size_t, const double rating) const
Denormalize computed rating by adding mean. 
 
Linear algebra utility functions, generally performed on matrices or vectors. 
 
void Normalize(arma::sp_mat &cleanedData)
Normalize the data by subtracting the mean of all existing ratings. 
 
double Mean() const
Return mean. 
 
The core includes that mlpack expects; standard C++ includes and Armadillo. 
 
void Denormalize(const arma::Mat< size_t > &, arma::vec &predictions) const
Denormalize computed rating by adding mean. 
 
This normalization class performs overall mean normalization on raw ratings. 
 
void Normalize(arma::mat &data)
Normalize the data by subtracting the mean of all existing ratings. 
 
void serialize(Archive &ar, const uint32_t)
Serialization.