MyMediaLite
3.02
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Interface for item recommenders. More...
Public Member Functions | |
void | AddFeedback (int user_id, int item_id) |
Add a positive feedback event and perform incremental training. | |
bool | CanPredict (int user_id, int item_id) |
Check whether a useful prediction (i.e. not using a fallback/default answer) can be made for a given user-item combination. | |
void | LoadModel (string filename) |
Get the model parameters from a file. | |
float | 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) |
Remove all feedback events by the given user-item combination. | |
void | RemoveItem (int item_id) |
Remove all feedback by one item. | |
void | RemoveUser (int user_id) |
Remove all feedback by one user. | |
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. |
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).
void AddFeedback | ( | int | user_id, |
int | item_id | ||
) |
Add a positive feedback event and perform incremental training.
user_id | the user ID |
item_id | the item ID |
Implemented in BPRMF, MostPopular, and IncrementalItemRecommender.
bool CanPredict | ( | int | user_id, |
int | item_id | ||
) | [inherited] |
Check whether a useful prediction (i.e. not using a fallback/default answer) can be made for a given user-item combination.
It is up to the recommender implementor to decide when a prediction is useful, and to document it accordingly.
user_id | the user ID |
item_id | the item ID |
Implemented in RatingPredictor, Ensemble, ItemRecommender, BiPolarSlopeOne, Constant, SlopeOne, GlobalAverage, UserAverage, ItemAverage, and Random.
void LoadModel | ( | string | filename | ) | [inherited] |
Get the model parameters from a file.
filename | the name of the file to read from |
Implemented in BPRMF, MatrixFactorization, BiasedMatrixFactorization, CoClustering, SVDPlusPlus, BPRLinear, FactorWiseMatrixFactorization, UserItemBaseline, SigmoidCombinedAsymmetricFactorModel, SigmoidSVDPlusPlus, BiPolarSlopeOne, SigmoidItemAsymmetricFactorModel, SigmoidUserAsymmetricFactorModel, ItemKNN, NaiveBayes, SlopeOne, MostPopularByAttributes, ItemAttributeSVM, MF, MostPopular, EntityAverage, KNN, Ensemble, GlobalAverage, ItemRecommender, WeightedEnsemble, RatingPredictor, KNN, Constant, Random, Random, and Zero.
float Predict | ( | int | user_id, |
int | item_id | ||
) | [inherited] |
Predict rating or score for a given user-item combination.
user_id | the user ID |
item_id | the item ID |
Implemented in BPRMF, BiasedMatrixFactorization, LatentFeatureLogLinearModel, TimeAwareBaseline, BPRMF_ItemMapping, MatrixFactorization, BPRLinear, BPRMF_UserMapping, FactorWiseMatrixFactorization, UserItemBaseline, CoClustering, NaiveBayes, SVDPlusPlus, SigmoidCombinedAsymmetricFactorModel, ItemAttributeSVM, SigmoidSVDPlusPlus, MF, MostPopularByAttributes, SigmoidItemAsymmetricFactorModel, SigmoidUserAsymmetricFactorModel, Ensemble, BiPolarSlopeOne, ItemRecommender, RatingPredictor, SlopeOne, ItemKNN, WeightedEnsemble, MostPopular, Constant, UserKNN, GlobalAverage, UserKNN, ItemKNN, UserAverage, ItemAverage, Random, WeightedItemKNN, Random, WeightedUserKNN, and Zero.
void RemoveFeedback | ( | int | user_id, |
int | item_id | ||
) |
Remove all feedback events by the given user-item combination.
user_id | the user ID |
item_id | the item ID |
Implemented in BPRMF, MostPopular, and IncrementalItemRecommender.
void RemoveItem | ( | int | item_id | ) |
Remove all feedback by one item.
item_id | the item ID |
Implemented in BPRMF, IncrementalItemRecommender, and MostPopular.
void RemoveUser | ( | int | user_id | ) |
Remove all feedback by one user.
user_id | the user ID |
Implemented in BPRMF, MostPopular, and IncrementalItemRecommender.
void SaveModel | ( | string | filename | ) | [inherited] |
Save the model parameters to a file.
filename | the name of the file to write to |
Implemented in BPRMF, MatrixFactorization, BiasedMatrixFactorization, CoClustering, SVDPlusPlus, BPRLinear, FactorWiseMatrixFactorization, UserItemBaseline, BiPolarSlopeOne, SigmoidCombinedAsymmetricFactorModel, NaiveBayes, SigmoidItemAsymmetricFactorModel, SigmoidUserAsymmetricFactorModel, SlopeOne, MostPopularByAttributes, ItemAttributeSVM, MF, EntityAverage, MostPopular, ItemRecommender, Ensemble, KNN, GlobalAverage, RatingPredictor, WeightedEnsemble, Constant, Random, KNN, Random, and Zero.
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 BPRMF, BiasedMatrixFactorization, BPRMF_Mapping, SVDPlusPlus, MatrixFactorization, CoClustering, SigmoidCombinedAsymmetricFactorModel, SigmoidItemAsymmetricFactorModel, TimeAwareBaseline, SigmoidUserAsymmetricFactorModel, LatentFeatureLogLinearModel, FactorWiseMatrixFactorization, SigmoidSVDPlusPlus, BPRLinear, UserItemBaseline, BPRMF_ItemMapping, SocialMF, BPRMF_UserMapping, NaiveBayes, TimeAwareBaselineWithFrequencies, WRMF, MultiCoreBPRMF, BPRMF_ItemMapping_Optimal, BPRMF_ItemMappingSVR, SoftMarginRankingMF, ItemAttributeSVM, BPRMF_UserMapping_Optimal, BPRMF_ItemMappingKNN, ItemRecommender, RatingPredictor, ItemKNN, UserKNN, UserAttributeKNN, WeightedBPRMF, UserKNNCosine, Constant, UserKNNPearson, ItemAttributeKNN, ItemAttributeKNN, UserAttributeKNN, WeightedItemKNN, ItemKNNPearson, WeightedUserKNN, and ItemKNNCosine.