Abstract class for rating predictors that keep the rating data in memory for training (and possibly prediction). More...
Public Member Functions | |
virtual void | AddRating (int user_id, int item_id, double rating) |
virtual 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 | |
abstract void | LoadModel (string filename) |
Get the model parameters from a file. | |
abstract double | Predict (int user_id, int item_id) |
Predict rating or score for a given user-item combination. | |
RatingPredictor () | |
Default constructor. | |
virtual void | RemoveItem (int item_id) |
virtual void | RemoveRating (int user_id, int item_id) |
virtual void | RemoveUser (int user_id) |
abstract void | SaveModel (string filename) |
Save the model parameters to a file. | |
string | ToString () |
Return a string representation of the recommender. | |
abstract 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 | AddItem (int item_id) |
virtual void | AddUser (int user_id) |
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 incremental updates | |
bool | UpdateUsers [get, set] |
true if users shall be updated when doing incremental updates |
Abstract class for rating predictors that keep the rating data in memory for training (and possibly prediction).
RatingPredictor | ( | ) |
Default constructor.
virtual 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 |
Implements IRecommender.
Reimplemented in BiPolarSlopeOne, GlobalAverage, ItemAverage, SlopeOne, and UserAverage.
Object Clone | ( | ) |
create a shallow copy of the object
virtual void InitModel | ( | ) | [protected, virtual] |
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, FactorWiseMatrixFactorization, MatrixFactorization, SlopeOne, and UserItemBaseline.
abstract void LoadModel | ( | string | filename | ) | [pure virtual] |
Get the model parameters from a file.
filename | the name of the file to read from |
Implements IRecommender.
Implemented in BiasedMatrixFactorization, BiPolarSlopeOne, EntityAverage, FactorWiseMatrixFactorization, GlobalAverage, ItemKNN, KNN, MatrixFactorization, SlopeOne, and UserItemBaseline.
abstract double Predict | ( | int | user_id, | |
int | item_id | |||
) | [pure virtual] |
Predict rating or score for a given user-item combination.
user_id | the user ID | |
item_id | the item ID |
Implements IRecommender.
Implemented in BiasedMatrixFactorization, BiPolarSlopeOne, FactorWiseMatrixFactorization, GlobalAverage, ItemAverage, ItemKNN, MatrixFactorization, SlopeOne, UserAverage, UserItemBaseline, and UserKNN.
abstract void SaveModel | ( | string | filename | ) | [pure virtual] |
Save the model parameters to a file.
filename | the name of the file to write to |
Implements IRecommender.
Implemented in BiasedMatrixFactorization, BiPolarSlopeOne, EntityAverage, FactorWiseMatrixFactorization, GlobalAverage, KNN, MatrixFactorization, SlopeOne, and UserItemBaseline.
string ToString | ( | ) | [inherited] |
Return a string representation of the recommender.
The ToString() method of recommenders should list the class name and all hyperparameters, separated by space characters.
Implemented in BPR_Linear, BPRMF, ItemAttributeKNN, ItemKNN, MostPopular, Random, UserAttributeKNN, UserKNN, WeightedItemKNN, WeightedUserKNN, WRMF, Zero, BiasedMatrixFactorization, BiasedMatrixFactorizationMAE, BiPolarSlopeOne, FactorWiseMatrixFactorization, GlobalAverage, ItemAttributeKNN, ItemAverage, ItemKNNCosine, ItemKNNPearson, MatrixFactorization, SlopeOne, UserAttributeKNN, UserAverage, UserItemBaseline, UserKNNCosine, and UserKNNPearson.
double max_rating [protected] |
The max rating value.
double min_rating [protected] |
The min rating value.
int MaxItemID [get, set] |
Maximum item ID.
virtual double MaxRating [get, set] |
The max rating value.
Implements IRatingPredictor.
int MaxUserID [get, set] |
Maximum user ID.
virtual double MinRating [get, set] |
The min rating value.
Implements IRatingPredictor.
bool UpdateItems [get, set] |
true if items shall be updated when doing incremental updates
Default is true. Set to false if you do not want any updates to the item model parameters when doing incremental updates.
bool UpdateUsers [get, set] |
true if users shall be updated when doing incremental updates
Default is true. Set to false if you do not want any updates to the user model parameters when doing incremental updates.