Public Member Functions
	RegularizedSVDFunction (const arma::mat &data, const size_t rank, const double lambda)
	Constructor for RegularizedSVDFunction class. More...

const arma::mat &	Dataset () const
	Return the dataset passed into the constructor. More...

double	Evaluate (const arma::mat &parameters) const
	Evaluates the cost function over all examples in the data. More...

double	Evaluate (const arma::mat &parameters, const size_t i) const
	Evaluates the cost function for one training example. More...

const arma::mat &	GetInitialPoint () const
	Return the initial point for the optimization. More...

void	Gradient (const arma::mat &parameters, arma::mat &gradient) const
	Evaluates the full gradient of the cost function over all the training examples. More...

double	Lambda () const
	Return the regularization parameters. More...

size_t	NumFunctions () const
	Return the number of training examples. Useful for SGD optimizer. More...

size_t	NumItems () const
	Return the number of items in the data. More...

size_t	NumUsers () const
	Return the number of users in the data. More...

size_t	Rank () const
	Return the rank used for the factorization. More...

Private Attributes
const arma::mat &	data
	Rating data. More...

arma::mat	initialPoint
	Initial parameter point. More...

double	lambda
	Regularization parameter for the optimization. More...

size_t	numItems
	Number of items in the given dataset. More...

size_t	numUsers
	Number of users in the given dataset. More...

size_t	rank
	Rank used for matrix factorization. More...

Detailed Description

Definition at line 22 of file regularized_svd_function.hpp.

Constructor & Destructor Documentation

mlpack::svd::RegularizedSVDFunction::RegularizedSVDFunction	(	const arma::mat &	data,
		const size_t	rank,
		const double	lambda
	)

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

data	Dataset for which SVD is calculated.
rank	Rank used for matrix factorization.
lambda	Regularization parameter used for optimization.

Member Function Documentation

const arma::mat& mlpack::svd::RegularizedSVDFunction::Dataset ( ) const

inline

Return the dataset passed into the constructor.

Definition at line 70 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

parameters Parameters(user/item matrices) of the decomposition.

double mlpack::svd::RegularizedSVDFunction::Evaluate	(	const arma::mat &	parameters,
		const size_t	i
	)		const

Evaluates the cost function for one training example.

Useful for the SGD optimizer abstraction which uses one training example at a time.

Parameters

parameters	Parameters(user/item matrices) of the decomposition.
i	Index of the training example to be used.

const arma::mat& mlpack::svd::RegularizedSVDFunction::GetInitialPoint ( ) const

inline

Return the initial point for the optimization.

Definition at line 67 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

parameters	Parameters(user/item matrices) of the decomposition.
gradient	Calculated gradient for the parameters.

double mlpack::svd::RegularizedSVDFunction::Lambda ( ) const

inline

Return the regularization parameters.

Definition at line 82 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 73 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 79 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 76 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 85 of file regularized_svd_function.hpp.

References rank.

Member Data Documentation

const arma::mat& mlpack::svd::RegularizedSVDFunction::data

private

Rating data.

Definition at line 89 of file regularized_svd_function.hpp.

Referenced by Dataset().

arma::mat mlpack::svd::RegularizedSVDFunction::initialPoint

private

Initial parameter point.

Definition at line 91 of file regularized_svd_function.hpp.

Referenced by GetInitialPoint().

double mlpack::svd::RegularizedSVDFunction::lambda

private

Regularization parameter for the optimization.

Definition at line 95 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 99 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 97 of file regularized_svd_function.hpp.

Referenced by NumUsers().

size_t mlpack::svd::RegularizedSVDFunction::rank

private

Rank used for matrix factorization.

Definition at line 93 of file regularized_svd_function.hpp.

Referenced by Rank().

The documentation for this class was generated from the following file:

src/mlpack/methods/regularized_svd/regularized_svd_function.hpp

Public Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation