NAME¶

mlpack::svd::RegularizedSVDFunction -

SYNOPSIS¶

Public Member Functions¶

RegularizedSVDFunction (const arma::mat &data, const size_t rank, const double lambda) Constructor for RegularizedSVDFunction class. const arma::mat & Dataset () const Return the dataset passed into the constructor. double Evaluate (const arma::mat &parameters) const Evaluates the cost function over all examples in the data. double Evaluate (const arma::mat &parameters, const size_t i) const Evaluates the cost function for one training example. const arma::mat & GetInitialPoint () const Return the initial point for the optimization. void Gradient (const arma::mat &parameters, arma::mat &gradient) const Evaluates the full gradient of the cost function over all the training examples. double Lambda () const Return the regularization parameters. size_t NumFunctions () const Return the number of training examples. Useful for SGD optimizer. size_t NumItems () const Return the number of items in the data. size_t NumUsers () const Return the number of users in the data. size_t Rank () const Return the rank used for the factorization.

Private Attributes¶

const arma::mat & data Rating data. arma::mat initialPoint Initial parameter point. double lambda Regularization parameter for the optimization. size_t numItems Number of items in the given dataset. size_t numUsers Number of users in the given dataset. size_t rank Rank used for matrix factorization.

Detailed Description¶

Definition at line 32 of file regularized_svd_function.hpp.

Constructor & Destructor Documentation¶

mlpack::svd::RegularizedSVDFunction::RegularizedSVDFunction (const arma::mat &data, const size_trank, const doublelambda)¶

Constructor for RegularizedSVDFunction class. The constructor calculates the number of users and items in the passed data. It also randomly initializes the parameter values. Parameters:

Member Function Documentation¶

const arma::mat& mlpack::svd::RegularizedSVDFunction::Dataset () const [inline]¶

Return the dataset passed into the constructor. Definition at line 80 of file regularized_svd_function.hpp. References data.

double mlpack::svd::RegularizedSVDFunction::Evaluate (const arma::mat &parameters) const¶

Evaluates the cost function over all examples in the data. Parameters:

double mlpack::svd::RegularizedSVDFunction::Evaluate (const arma::mat &parameters, const size_ti) const¶

Evaluates the cost function for one training example. Useful for the SGD optimizer abstraction which uses one training example at a time. Parameters:

const arma::mat& mlpack::svd::RegularizedSVDFunction::GetInitialPoint () const [inline]¶

Return the initial point for the optimization. Definition at line 77 of file regularized_svd_function.hpp. References initialPoint.

void mlpack::svd::RegularizedSVDFunction::Gradient (const arma::mat &parameters, arma::mat &gradient) const¶

Evaluates the full gradient of the cost function over all the training examples. Parameters:

double mlpack::svd::RegularizedSVDFunction::Lambda () const [inline]¶

Return the regularization parameters. Definition at line 92 of file regularized_svd_function.hpp. References lambda.

size_t mlpack::svd::RegularizedSVDFunction::NumFunctions () const [inline]¶

Return the number of training examples. Useful for SGD optimizer. Definition at line 83 of file regularized_svd_function.hpp.

size_t mlpack::svd::RegularizedSVDFunction::NumItems () const [inline]¶

Return the number of items in the data. Definition at line 89 of file regularized_svd_function.hpp. References numItems.

size_t mlpack::svd::RegularizedSVDFunction::NumUsers () const [inline]¶

Return the number of users in the data. Definition at line 86 of file regularized_svd_function.hpp. References numUsers.

size_t mlpack::svd::RegularizedSVDFunction::Rank () const [inline]¶

Return the rank used for the factorization. Definition at line 95 of file regularized_svd_function.hpp. References rank.

Member Data Documentation¶

const arma::mat& mlpack::svd::RegularizedSVDFunction::data [private]¶

Rating data. Definition at line 99 of file regularized_svd_function.hpp. Referenced by Dataset().

arma::mat mlpack::svd::RegularizedSVDFunction::initialPoint [private]¶

Initial parameter point. Definition at line 101 of file regularized_svd_function.hpp. Referenced by GetInitialPoint().

double mlpack::svd::RegularizedSVDFunction::lambda [private]¶

Regularization parameter for the optimization. Definition at line 105 of file regularized_svd_function.hpp. Referenced by Lambda().

size_t mlpack::svd::RegularizedSVDFunction::numItems [private]¶

Number of items in the given dataset. Definition at line 109 of file regularized_svd_function.hpp. Referenced by NumItems().

size_t mlpack::svd::RegularizedSVDFunction::numUsers [private]¶

Number of users in the given dataset. Definition at line 107 of file regularized_svd_function.hpp. Referenced by NumUsers().

size_t mlpack::svd::RegularizedSVDFunction::rank [private]¶

Rank used for matrix factorization. Definition at line 103 of file regularized_svd_function.hpp. Referenced by Rank().

Author¶

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