Base class for item recommenders that use some kind of kNN model. More...
Public Member Functions | |
virtual void | AddFeedback (int user_id, int item_id) |
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 | |
override 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. | |
virtual void | RemoveFeedback (int user_id, int item_id) |
virtual void | RemoveItem (int item_id) |
virtual void | RemoveUser (int user_id) |
override 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. | |
Protected Member Functions | |
virtual void | AddItem (int item_id) |
virtual void | AddUser (int user_id) |
Protected Attributes | |
CorrelationMatrix | correlation |
Correlation matrix over some kind of entity. | |
uint | k = 80 |
The number of neighbors to take into account for prediction. | |
int[][] | nearest_neighbors |
Precomputed nearest neighbors. | |
Properties | |
virtual IPosOnlyFeedback | Feedback [get, set] |
the feedback data to be used for training | |
uint | K [get, set] |
The number of neighbors to take into account for prediction. | |
int | MaxItemID [get, set] |
Maximum item ID. | |
int | MaxUserID [get, set] |
Maximum user ID. |
Base class for item recommenders that use some kind of kNN model.
virtual bool CanPredict | ( | int | user_id, | |
int | item_id | |||
) | [virtual, inherited] |
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.
Object Clone | ( | ) | [inherited] |
create a shallow copy of the object
override void LoadModel | ( | string | filename | ) | [virtual] |
Get the model parameters from a file.
filename | the name of the file to read from |
Implements ItemRecommender.
abstract double Predict | ( | int | user_id, | |
int | item_id | |||
) | [pure virtual, inherited] |
Predict rating or score for a given user-item combination.
user_id | the user ID | |
item_id | the item ID |
Implements IRecommender.
Implemented in BPR_Linear, BPRMF, ItemKNN, MF, MostPopular, Random, UserKNN, WeightedItemKNN, WeightedUserKNN, and Zero.
override void SaveModel | ( | string | filename | ) | [virtual] |
Save the model parameters to a file.
filename | the name of the file to write to |
Implements ItemRecommender.
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.
CorrelationMatrix correlation [protected] |
Correlation matrix over some kind of entity.
uint k = 80 [protected] |
The number of neighbors to take into account for prediction.
int [][] nearest_neighbors [protected] |
Precomputed nearest neighbors.
virtual IPosOnlyFeedback Feedback [get, set, inherited] |
the feedback data to be used for training
uint K [get, set] |
The number of neighbors to take into account for prediction.
int MaxItemID [get, set, inherited] |
Maximum item ID.
int MaxUserID [get, set, inherited] |
Maximum user ID.