Aakash-kaushik/mlpack/regularized__svd_8hpp_source.html

 #ifndef MLPACK_METHODS_REGULARIZED_SVD_REGULARIZED_SVD_HPP
 #define MLPACK_METHODS_REGULARIZED_SVD_REGULARIZED_SVD_HPP

 #include <mlpack/prereqs.hpp>
 #include <ensmallen.hpp>
 #include <mlpack/methods/cf/cf.hpp>

 #include "regularized_svd_function.hpp"

 namespace mlpack {
 namespace svd {

 template<typename OptimizerType = ens::StandardSGD>
 class RegularizedSVD
 {
  public:
   RegularizedSVD(const size_t iterations = 10,
                  const double alpha = 0.01,
                  const double lambda = 0.02);

   void Apply(const arma::mat& data,
              const size_t rank,
              arma::mat& u,
              arma::mat& v);

  private:
   size_t iterations;
   double alpha;
   double lambda;
 };

 } // namespace svd
 } // namespace mlpack

 // Include implementation.
 #include "regularized_svd_impl.hpp"

 #endif
regularized_svd_impl.hpp

mlpack::svd::RegularizedSVD
Regularized SVD is a matrix factorization technique that seeks to reduce the error on the training se...
Definition: regularized_svd.hpp:58

mlpack::svd::RegularizedSVD::RegularizedSVD
RegularizedSVD(const size_t iterations=10, const double alpha=0.01, const double lambda=0.02)
Constructor for Regularized SVD.
Definition: regularized_svd_impl.hpp:20

data

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

cf.hpp

prereqs.hpp
The core includes that mlpack expects; standard C++ includes and Armadillo.

regularized_svd_function.hpp

mlpack::svd::RegularizedSVD::Apply
void Apply(const arma::mat &data, const size_t rank, arma::mat &u, arma::mat &v)
Obtains the user and item matrices using the provided data and rank.
Definition: regularized_svd_impl.hpp:31