C# Class MyMediaLite.RatingPrediction.FactorWiseMatrixFactorization

Matrix factorization with factor-wise learning

Robert Bell, Yehuda Koren, Chris Volinsky: Modeling Relationships at Multiple Scales to Improve Accuracy of Large Recommender Systems, ACM Int. Conference on Knowledge Discovery and Data Mining (KDD'07), 2007. This recommender does NOT support incremental updates.

Inheritance: RatingPredictor, IIterativeModel

Afficher le fichier Open project: zenogantner/MML-KDD

Méthodes publiques

Méthode	Description
ComputeFit ( ) : double
FactorWiseMatrixFactorization ( ) : System	Default constructor
Iterate ( ) : void
LoadModel ( string filename ) : void
Predict ( int user_id, int item_id ) : double	Predict the rating of a given user for a given item If the user or the item are not known to the recommender, the global effects prediction is returned. To avoid this behavior for unknown entities, use CanPredict() to check before.
SaveModel ( string filename ) : void
ToString ( ) : string
Train ( ) : void

Method Details

ComputeFit() public méthode

public ComputeFit ( ) : double
Résultat	double

FactorWiseMatrixFactorization() public méthode

Default constructor

public FactorWiseMatrixFactorization ( ) : System
Résultat	System

Iterate() public méthode

public Iterate ( ) : void
Résultat	void

LoadModel() public méthode

public LoadModel ( string filename ) : void
filename	string
Résultat	void

Predict() public méthode

Predict the rating of a given user for a given item

If the user or the item are not known to the recommender, the global effects prediction is returned. To avoid this behavior for unknown entities, use CanPredict() to check before.

public Predict ( int user_id, int item_id ) : double
user_id	int	the user ID
item_id	int	the item ID
Résultat	double

SaveModel() public méthode

public SaveModel ( string filename ) : void
filename	string
Résultat	void

ToString() public méthode

public ToString ( ) : string
Résultat	string

Train() public méthode

public Train ( ) : void
Résultat	void