Uses the average rating value over all ratings for prediction. More...
Public Member Functions | |
virtual void | Add (int user_id, int item_id, double rating) |
virtual void | AddItem (int item_id) |
virtual void | AddUser (int user_id) |
override bool | CanPredict (int user_id, int item_id) |
Check whether a useful prediction can be made for a given user-item combination. | |
Object | Clone () |
create a shallow copy of the object | |
override void | LoadModel (string filename) |
Get the model parameters from a file. | |
override double | Predict (int user_id, int item_id) |
Predict rating or score for a given user-item combination. | |
virtual void | RemoveItem (int item_id) |
virtual void | RemoveRating (int user_id, int item_id) |
virtual void | RemoveUser (int user_id) |
override void | SaveModel (string filename) |
Save the model parameters to a file. | |
override string | ToString () |
Return a string representation of the recommender. | |
override void | Train () |
Learn the model parameters of the recommender from the training data. | |
virtual void | UpdateRating (int user_id, int item_id, double rating) |
Protected Member Functions | |
virtual void | InitModel () |
Inits the recommender model. | |
Protected Attributes | |
double | max_rating |
The max rating value. | |
double | min_rating |
The min rating value. | |
IRatings | ratings |
rating data | |
Properties | |
int | MaxItemID [get, set] |
Maximum item ID. | |
virtual double | MaxRating [get, set] |
The max rating value. | |
int | MaxUserID [get, set] |
Maximum user ID. | |
virtual double | MinRating [get, set] |
The min rating value. | |
virtual IRatings | Ratings [get, set] |
The rating data. | |
bool | UpdateItems [get, set] |
true if items shall be updated when doing online updates | |
bool | UpdateUsers [get, set] |
true if users shall be updated when doing online updates |
Uses the average rating value over all ratings for prediction.
This engine does NOT support online updates.
override bool CanPredict | ( | int | user_id, | |
int | item_id | |||
) | [virtual] |
Check whether a useful prediction can be made for a given user-item combination.
user_id | the user ID | |
item_id | the item ID |
Reimplemented from RatingPredictor.
Object Clone | ( | ) | [inherited] |
create a shallow copy of the object
virtual void InitModel | ( | ) | [protected, virtual, inherited] |
Inits the recommender model.
This method is called by the Train() method. When overriding, please call base.InitModel() to get the functions performed in the base class.
Reimplemented in BiasedMatrixFactorization, BiPolarSlopeOne, MatrixFactorization, SlopeOne, and UserItemBaseline.
override void LoadModel | ( | string | filename | ) | [virtual] |
Get the model parameters from a file.
filename | the name of the file to read from |
Implements RatingPredictor.
override double Predict | ( | int | user_id, | |
int | item_id | |||
) | [virtual] |
Predict rating or score for a given user-item combination.
user_id | the user ID | |
item_id | the item ID |
Implements RatingPredictor.
override void SaveModel | ( | string | filename | ) | [virtual] |
Save the model parameters to a file.
filename | the name of the file to write to |
Implements RatingPredictor.
override string ToString | ( | ) |
Return a string representation of the recommender.
The ToString() method of recommenders should list the class name and all hyperparameters, separated by space characters.
Implements IRecommender.
double max_rating [protected, inherited] |
The max rating value.
double min_rating [protected, inherited] |
The min rating value.
int MaxItemID [get, set, inherited] |
Maximum item ID.
Maximum item ID
virtual double MaxRating [get, set, inherited] |
int MaxUserID [get, set, inherited] |
Maximum user ID.
Maximum user ID
virtual double MinRating [get, set, inherited] |
bool UpdateItems [get, set, inherited] |
true if items shall be updated when doing online updates
true if items shall be updated when doing online updates
bool UpdateUsers [get, set, inherited] |
true if users shall be updated when doing online updates
true if users shall be updated when doing online updates