Scroll to navigation

mlpack::svd::RegularizedSVD< OptimizerType >(3) MLPACK mlpack::svd::RegularizedSVD< OptimizerType >(3)

NAME

mlpack::svd::RegularizedSVD< OptimizerType > -

SYNOPSIS

Public Member Functions


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.

Private Attributes


double alpha
 
Learning rate for the SGD optimizer. const arma::mat & data
 
Rating data. size_t iterations
 
Number of optimization iterations. double lambda
 
Regularization parameter for the optimization. mlpack::optimization::SGD
 
< RegularizedSVDFunction > optimizer"
 
Default SGD optimizer for the class. size_t rank
 
Rank used for matrix factorization. RegularizedSVDFunction rSVDFunc
 
Function that will be held by the optimizer.

Detailed Description

template<template< typename > class OptimizerType = mlpack::optimization::SGD>class mlpack::svd::RegularizedSVD< OptimizerType >

Definition at line 37 of file regularized_svd.hpp.

Constructor & Destructor Documentation

template<template< typename > class OptimizerType = mlpack::optimization::SGD> mlpack::svd::RegularizedSVD< OptimizerType >:: RegularizedSVD (const arma::mat &data, arma::mat &u, arma::mat &v, const size_trank, const size_titerations = 10, const doublealpha = 0.01, const doublelambda = 0.02)

Constructor for Regularized SVD. Obtains the user and item matrices after training on the passed data. The constructor initiates an object of class RegularizedSVDFunction for optimization. It uses the SGD optimizer by default. The optimizer uses a template specialization of Optimize().
Parameters:
data Dataset for which SVD is calculated.
 
u User matrix in the matrix decomposition.
 
v Item matrix in the matrix decomposition.
 
rank Rank used for matrix factorization.
 
iterations Number of optimization iterations.
 
lambda Regularization parameter for the optimization.

Member Data Documentation

template<template< typename > class OptimizerType = mlpack::optimization::SGD> double mlpack::svd::RegularizedSVD< OptimizerType >::alpha [private]

Learning rate for the SGD optimizer.
Definition at line 70 of file regularized_svd.hpp.

template<template< typename > class OptimizerType = mlpack::optimization::SGD> const arma::mat& mlpack::svd::RegularizedSVD< OptimizerType >::data [private]

Rating data.
Definition at line 64 of file regularized_svd.hpp.

template<template< typename > class OptimizerType = mlpack::optimization::SGD> size_t mlpack::svd::RegularizedSVD< OptimizerType >::iterations [private]

Number of optimization iterations.
Definition at line 68 of file regularized_svd.hpp.

template<template< typename > class OptimizerType = mlpack::optimization::SGD> double mlpack::svd::RegularizedSVD< OptimizerType >::lambda [private]

Regularization parameter for the optimization.
Definition at line 72 of file regularized_svd.hpp.

template<template< typename > class OptimizerType = mlpack::optimization::SGD> mlpack::optimization::SGD< RegularizedSVDFunction> mlpack::svd::RegularizedSVD< OptimizerType >::optimizer [private]

Default SGD optimizer for the class.
Definition at line 76 of file regularized_svd.hpp.

template<template< typename > class OptimizerType = mlpack::optimization::SGD> size_t mlpack::svd::RegularizedSVD< OptimizerType >::rank [private]

Rank used for matrix factorization.
Definition at line 66 of file regularized_svd.hpp.

template<template< typename > class OptimizerType = mlpack::optimization::SGD> RegularizedSVDFunction mlpack::svd::RegularizedSVD< OptimizerType >::rSVDFunc [private]

Function that will be held by the optimizer.
Definition at line 74 of file regularized_svd.hpp.

Author

Generated automatically by Doxygen for MLPACK from the source code.
Tue Sep 9 2014 Version 1.0.10