IIncrementalItemRecommender Interface Reference

Interface for item recommenders. More...

Inheritance diagram for IIncrementalItemRecommender:
IRecommender IncrementalItemRecommender MF MostPopular BPRMF WRMF

List of all members.

Public Member Functions

void AddFeedback (int user_id, int item_id)
bool CanPredict (int user_id, int item_id)
 Check whether a useful prediction can be made for a given user-item combination.
void LoadModel (string filename)
 Get the model parameters from a file.
double Predict (int user_id, int item_id)
 Predict rating or score for a given user-item combination.
void RemoveFeedback (int user_id, int item_id)
void RemoveItem (int item_id)
void RemoveUser (int user_id)
void SaveModel (string filename)
 Save the model parameters to a file.
string ToString ()
 Return a string representation of the recommender.
void Train ()
 Learn the model parameters of the recommender from the training data.

Detailed Description

Interface for item recommenders.

Item prediction or item recommendation is the task of predicting items (movies, books, products, videos, jokes) that a user may like, based on past user behavior (and possibly other information).

See also http://recsyswiki/wiki/Item_prediction


Member Function Documentation

bool CanPredict ( int  user_id,
int  item_id 
) [inherited]

Check whether a useful prediction can be made for a given user-item combination.

Parameters:
user_id the user ID
item_id the item ID
Returns:
true if a useful prediction can be made, false otherwise

Implemented in Ensemble, ItemRecommender, BiPolarSlopeOne, GlobalAverage, ItemAverage, RatingPredictor, SlopeOne, and UserAverage.

void LoadModel ( string  filename  )  [inherited]
double Predict ( int  user_id,
int  item_id 
) [inherited]

Predict rating or score for a given user-item combination.

Parameters:
user_id the user ID
item_id the item ID
Returns:
the predicted score/rating for the given user-item combination

Implemented in Ensemble, WeightedEnsemble, BPR_Linear, BPRMF, ItemKNN, ItemRecommender, MF, MostPopular, Random, UserKNN, WeightedItemKNN, WeightedUserKNN, Zero, BiasedMatrixFactorization, BiPolarSlopeOne, FactorWiseMatrixFactorization, GlobalAverage, ItemAverage, ItemKNN, MatrixFactorization, RatingPredictor, SlopeOne, TimeAwareBaseline, UserAverage, UserItemBaseline, and UserKNN.

void SaveModel ( string  filename  )  [inherited]
string ToString (  )  [inherited]

The documentation for this interface was generated from the following file:
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