MyMediaLite
3.11
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Interface for recommenders that take a binary relation over users into account More...
Public Member Functions | |
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 More... | |
void | LoadModel (string filename) |
Get the model parameters from a file More... | |
float | Predict (int user_id, int item_id) |
Predict rating or score for a given user-item combination More... | |
IList< Tuple< int, float > > | Recommend (int user_id, int n=-1, ICollection< int > ignore_items=null, ICollection< int > candidate_items=null) |
Recommend items for a given user More... | |
void | SaveModel (string filename) |
Save the model parameters to a file More... | |
string | ToString () |
Return a string representation of the recommender More... | |
void | Train () |
Learn the model parameters of the recommender from the training data More... | |
Properties | |
int | NumUsers [get] |
IBooleanMatrix | UserRelation [get, set] |
Interface for recommenders that take a binary relation over users into account
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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 Ensemble, ExternalItemRecommender, ExternalRatingPredictor, BiPolarSlopeOne, Recommender, SlopeOne, Constant, GlobalAverage, UserAverage, ItemAverage, and Random.
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inherited |
Get the model parameters from a file
filename | the name of the file to read from |
Implemented in BPRMF, MatrixFactorization, BiasedMatrixFactorization, BPRSLIM, CoClustering, LeastSquareSLIM, SVDPlusPlus, UserItemBaseline, FactorWiseMatrixFactorization, SigmoidCombinedAsymmetricFactorModel, MF, SigmoidSVDPlusPlus, BiPolarSlopeOne, SigmoidItemAsymmetricFactorModel, SigmoidUserAsymmetricFactorModel, KNN, KNN, MostPopular, NaiveBayes, SlopeOne, SLIM, MostPopularByAttributes, Recommender, EntityAverage, Ensemble, WeightedEnsemble, GlobalAverage, ExternalItemRecommender, ExternalRatingPredictor, Constant, Random, Random, and Zero.
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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, LeastSquareSLIM, MatrixFactorization, TimeAwareBaseline, FactorWiseMatrixFactorization, GSVDPlusPlus, MF, UserItemBaseline, CoClustering, NaiveBayes, SVDPlusPlus, SLIM, SigmoidCombinedAsymmetricFactorModel, MostPopularByAttributes, SigmoidSVDPlusPlus, SigmoidItemAsymmetricFactorModel, SigmoidUserAsymmetricFactorModel, Ensemble, MostPopular, BiPolarSlopeOne, ExternalItemRecommender, ExternalRatingPredictor, ItemKNN, ItemKNN, UserKNN, SlopeOne, WeightedEnsemble, Constant, UserKNN, GlobalAverage, UserAverage, ItemAverage, Recommender, Random, Random, and Zero.
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inherited |
Recommend items for a given user
user_id | the user ID |
n | the number of items to recommend, -1 for as many as possible |
ignore_items | collection if items that should not be returned; if null, use empty collection |
candidate_items | the candidate items to choose from; if null, use all items |
Implemented in WeightedEnsemble, and Ensemble.
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inherited |
Save the model parameters to a file
filename | the name of the file to write to |
Implemented in BPRMF, MatrixFactorization, BiasedMatrixFactorization, BPRSLIM, CoClustering, LeastSquareSLIM, SVDPlusPlus, UserItemBaseline, FactorWiseMatrixFactorization, BiPolarSlopeOne, SigmoidCombinedAsymmetricFactorModel, MF, NaiveBayes, SigmoidItemAsymmetricFactorModel, SigmoidUserAsymmetricFactorModel, SlopeOne, KNN, MostPopular, KNN, SLIM, Recommender, MostPopularByAttributes, EntityAverage, Ensemble, WeightedEnsemble, ExternalItemRecommender, ExternalRatingPredictor, GlobalAverage, Constant, Random, Random, and Zero.
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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, SVDPlusPlus, MatrixFactorization, SigmoidCombinedAsymmetricFactorModel, CoClustering, BPRSLIM, SigmoidItemAsymmetricFactorModel, LeastSquareSLIM, TimeAwareBaseline, SigmoidUserAsymmetricFactorModel, LatentFeatureLogLinearModel, FactorWiseMatrixFactorization, UserItemBaseline, SigmoidSVDPlusPlus, SocialMF, NaiveBayes, WRMF, KNN, KNN, MostPopular, TimeAwareBaselineWithFrequencies, SoftMarginRankingMF, Recommender, ExternalItemRecommender, ExternalRatingPredictor, WeightedBPRMF, MultiCoreBPRMF, and Constant.
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inherited |
Learn the model parameters of the recommender from the training data
Implemented in BiasedMatrixFactorization, TimeAwareBaseline, BPRMF, KNN, MatrixFactorization, KNN, LatentFeatureLogLinearModel, CoClustering, BiPolarSlopeOne, FactorWiseMatrixFactorization, Recommender, BPRSLIM, Ensemble, SlopeOne, UserItemBaseline, LeastSquareSLIM, TimeAwareBaselineWithFrequencies, SVDPlusPlus, GSVDPlusPlus, SLIM, NaiveBayes, SigmoidCombinedAsymmetricFactorModel, MF, MostPopularByAttributes, SigmoidItemAsymmetricFactorModel, SigmoidUserAsymmetricFactorModel, SigmoidSVDPlusPlus, MostPopular, ExternalItemRecommender, ExternalRatingPredictor, MultiCoreBPRMF, WeightedBPRMF, WeightedEnsemble, Constant, ItemKNN, UserKNN, GlobalAverage, UserAverage, ItemAverage, Random, Random, and Zero.
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get |
Number of users
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getset |
The binary user relation