23 #ifndef __MLPACK_METHODS_REGULARIZED_SVD_REGULARIZED_SVD_HPP
24 #define __MLPACK_METHODS_REGULARIZED_SVD_REGULARIZED_SVD_HPP
59 const double alpha = 0.01,
60 const double lambda = 0.02);
83 #include "regularized_svd_impl.hpp"
size_t iterations
Number of optimization iterations.
const arma::mat & data
Rating data.
Linear algebra utility functions, generally performed on matrices or vectors.
size_t rank
Rank used for matrix factorization.
double lambda
Regularization parameter for the optimization.
double alpha
Learning rate for the SGD optimizer.
RegularizedSVDFunction rSVDFunc
Function that will be held by the optimizer.
RegularizedSVD(const arma::mat &data, arma::mat &u, arma::mat &v, const size_t rank, const size_t iterations=10, const double alpha=0.01, const double lambda=0.02)
Constructor for Regularized SVD.
Stochastic Gradient Descent is a technique for minimizing a function which can be expressed as a sum ...
mlpack::optimization::SGD< RegularizedSVDFunction > optimizer
Default SGD optimizer for the class.