Implementation of the SVDPlusPlus policy to act as a wrapper when accessing SVDPlusPlus from within CFType. More...

Public Member Functions
	SVDPlusPlusPolicy (const size_t maxIterations=10, const double alpha=0.001, const double lambda=0.1)
	Use SVDPlusPlus method to perform collaborative filtering. More...

double	Alpha () const
	Get learning rate. More...

double &	Alpha ()
	Modify learning rate. More...

void	Apply (const arma::mat &data, const arma::sp_mat &, const size_t rank, const size_t maxIterations, const double, const bool)
	Apply Collaborative Filtering to the provided data set using the svdplusplus. More...

template < typename NeighborSearchPolicy >
void	GetNeighborhood (const arma::Col< size_t > &users, const size_t numUsersForSimilarity, arma::Mat< size_t > &neighborhood, arma::mat &similarities) const
	Get the neighborhood and corresponding similarities for a set of users. More...

double	GetRating (const size_t user, const size_t item) const
	Return predicted rating given user ID and item ID. More...

void	GetRatingOfUser (const size_t user, arma::vec &rating) const
	Get predicted ratings for a user. More...

const arma::mat &	H () const
	Get the User Matrix. More...

const arma::sp_mat &	ImplicitData () const
	Get Implicit Feedback Data. More...

double	Lambda () const
	Get regularization parameter. More...

double &	Lambda ()
	Modify regularization parameter. More...

size_t	MaxIterations () const
	Get the number of iterations. More...

size_t &	MaxIterations ()
	Modify the number of iterations. More...

const arma::vec &	P () const
	Get the Item Bias Vector. More...

const arma::vec &	Q () const
	Get the User Bias Vector. More...

template < typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialization. More...

const arma::mat &	W () const
	Get the Item Matrix. More...

const arma::mat &	Y () const
	Get the Item Implicit Matrix. More...

Detailed Description

Implementation of the SVDPlusPlus policy to act as a wrapper when accessing SVDPlusPlus from within CFType.

An example of how to use SVDPlusPlusPolicy in CF is shown below:

extern arma::mat data; // data is a (user, item, rating) table.
// Users for whom recommendations are generated.
extern arma::Col<size_t> users;
arma::Mat<size_t> recommendations; // Resulting recommendations.
CFType<SVDPlusPlusPolicy> cf(data);
// Generate 10 recommendations for all users.
cf.GetRecommendations(10, recommendations);

Definition at line 41 of file svdplusplus_method.hpp.

Constructor & Destructor Documentation

◆ SVDPlusPlusPolicy()

SVDPlusPlusPolicy	(	const size_t	maxIterations = `10`,
		const double	alpha = `0.001`,
		const double	lambda = `0.1`
	)

inline

Use SVDPlusPlus method to perform collaborative filtering.

Parameters

maxIterations	Number of iterations.
alpha	Learning rate for optimization.
lambda	Regularization parameter for optimization.

Definition at line 51 of file svdplusplus_method.hpp.

Member Function Documentation

◆ Alpha() [1/2]

double Alpha ( ) const

inline

Get learning rate.

Definition at line 193 of file svdplusplus_method.hpp.

◆ Alpha() [2/2]

double& Alpha ( )

inline

Modify learning rate.

Definition at line 195 of file svdplusplus_method.hpp.

◆ Apply()

void Apply	(	const arma::mat &	data,
		const arma::sp_mat &	,
		const size_t	rank,
		const size_t	maxIterations,
		const double	,
		const bool
	)

inline

Apply Collaborative Filtering to the provided data set using the svdplusplus.

Parameters

data	Data matrix: dense matrix (coordinate lists) or sparse matrix(cleaned).
*	(cleanedData) item user table in form of sparse matrix.
rank	Rank parameter for matrix factorization.
maxIterations	Maximum number of iterations.
*	(minResidue) Residue required to terminate.
*	(mit) Whether to terminate only when maxIterations is reached.

Definition at line 73 of file svdplusplus_method.hpp.

References SVDPlusPlus< OptimizerType >::Apply(), and SVDPlusPlus< OptimizerType >::CleanData().

◆ GetNeighborhood()

void GetNeighborhood	(	const arma::Col< size_t > &	users,
		const size_t	numUsersForSimilarity,
		arma::Mat< size_t > &	neighborhood,
		arma::mat &	similarities
	)		const

inline

Get the neighborhood and corresponding similarities for a set of users.

Template Parameters

NeighborSearchPolicy The policy to perform neighbor search.

Parameters

users	Users whose neighborhood is to be computed.
numUsersForSimilarity	The number of neighbors returned for each user.
neighborhood	Neighbors represented by user IDs.
similarities	Similarity between each user and each of its neighbors.

Definition at line 157 of file svdplusplus_method.hpp.

◆ GetRating()

double GetRating	(	const size_t	user,
		const size_t	item
	)		const

inline

Return predicted rating given user ID and item ID.

Parameters

user	User ID.
item	Item ID.

Definition at line 96 of file svdplusplus_method.hpp.

◆ GetRatingOfUser()

void GetRatingOfUser	(	const size_t	user,
		arma::vec &	rating
	)		const

inline

Get predicted ratings for a user.

Parameters

user	User ID.
rating	Resulting rating vector.

Definition at line 124 of file svdplusplus_method.hpp.

◆ H()

const arma::mat& H ( ) const

inline

Get the User Matrix.

Definition at line 177 of file svdplusplus_method.hpp.

◆ ImplicitData()

const arma::sp_mat& ImplicitData ( ) const

inline

Get Implicit Feedback Data.

Definition at line 185 of file svdplusplus_method.hpp.

◆ Lambda() [1/2]

double Lambda ( ) const

inline

Get regularization parameter.

Definition at line 198 of file svdplusplus_method.hpp.

◆ Lambda() [2/2]

double& Lambda ( )

inline

Modify regularization parameter.

Definition at line 200 of file svdplusplus_method.hpp.

◆ MaxIterations() [1/2]

size_t MaxIterations ( ) const

inline

Get the number of iterations.

Definition at line 188 of file svdplusplus_method.hpp.

◆ MaxIterations() [2/2]

size_t& MaxIterations ( )

inline

Modify the number of iterations.

Definition at line 190 of file svdplusplus_method.hpp.

◆ P()

const arma::vec& P ( ) const

inline

Get the Item Bias Vector.

Definition at line 181 of file svdplusplus_method.hpp.

◆ Q()

const arma::vec& Q ( ) const

inline

Get the User Bias Vector.

Definition at line 179 of file svdplusplus_method.hpp.

◆ serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

inline

Serialization.

Definition at line 206 of file svdplusplus_method.hpp.

◆ W()

const arma::mat& W ( ) const

inline

Get the Item Matrix.

Definition at line 175 of file svdplusplus_method.hpp.

◆ Y()

const arma::mat& Y ( ) const

inline

Get the Item Implicit Matrix.

Definition at line 183 of file svdplusplus_method.hpp.

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

/home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/cf/decomposition_policies/svdplusplus_method.hpp

Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ SVDPlusPlusPolicy()

Member Function Documentation

◆ Alpha() [1/2]

◆ Alpha() [2/2]

◆ Apply()

◆ GetNeighborhood()

◆ GetRating()

◆ GetRatingOfUser()

◆ H()

◆ ImplicitData()

◆ Lambda() [1/2]

◆ Lambda() [2/2]

◆ MaxIterations() [1/2]

◆ MaxIterations() [2/2]

◆ P()

◆ Q()

◆ serialize()

◆ W()

◆ Y()