15 #ifndef __MLPACK_METHODS_REGULARIZED_SVD_REGULARIZED_SVD_HPP
16 #define __MLPACK_METHODS_REGULARIZED_SVD_REGULARIZED_SVD_HPP
78 const double alpha = 0.01,
79 const double lambda = 0.02);
89 void Apply(
const arma::mat& data,
122 #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.
double lambda
Regularization parameter for the optimization.
double alpha
Learning rate for the SGD optimizer.
static const bool UsesCoordinateList
If true, then the passed data matrix is used for factorizer.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.
Include all of the base components required to write MLPACK methods, and the main MLPACK Doxygen docu...
Stochastic Gradient Descent is a technique for minimizing a function which can be expressed as a sum ...
Template class for factorizer traits.