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,
113 static const bool UsesCoordinateList =
true;
120 #include "regularized_svd_impl.hpp" size_t iterations
Number of optimization iterations.
Regularized SVD is a matrix factorization technique that seeks to reduce the error on the training se...
RegularizedSVD(const size_t iterations=10, const double alpha=0.01, const double lambda=0.02)
Constructor for Regularized SVD.
Linear algebra utility functions, generally performed on matrices or vectors.
The core includes that mlpack expects; standard C++ includes and Armadillo.
double lambda
Regularization parameter for the optimization.
double alpha
Learning rate for the SGD optimizer.
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.