13 #ifndef MLPACK_METHODS_REGULARIZED_SVD_REGULARIZED_SVD_HPP
14 #define MLPACK_METHODS_REGULARIZED_SVD_REGULARIZED_SVD_HPP
76 const double alpha = 0.01,
77 const double lambda = 0.02);
87 void Apply(
const arma::mat& data,
120 #include "regularized_svd_impl.hpp"
Regularized SVD is a matrix factorization technique that seeks to reduce the error on the training se...
static const bool UsesCoordinateList
If true, then the passed data matrix is used for factorizer.Apply().
The core includes that mlpack expects; standard C++ includes and Armadillo.
RegularizedSVD(const size_t iterations=10, const double alpha=0.01, const double lambda=0.02)
Constructor for Regularized SVD.
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.
Stochastic Gradient Descent is a technique for minimizing a function which can be expressed as a sum ...
Template class for factorizer traits.