C# 클래스 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.
상속: RatingPredictor, IIterativeModel
파일 보기 프로젝트 열기: zenogantner/MML-KDD

공개 메소드들

메소드 설명
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

메소드 상세

ComputeFit() 공개 메소드

public ComputeFit ( ) : double
리턴 double

FactorWiseMatrixFactorization() 공개 메소드

Default constructor
public FactorWiseMatrixFactorization ( ) : System
리턴 System

Iterate() 공개 메소드

public Iterate ( ) : void
리턴 void

LoadModel() 공개 메소드

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

Predict() 공개 메소드

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
리턴 double

SaveModel() 공개 메소드

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

ToString() 공개 메소드

public ToString ( ) : string
리턴 string

Train() 공개 메소드

public Train ( ) : void
리턴 void