IRecommender Interface Reference

Generic interface for simple recommenders More...

Inheritance diagram for IRecommender:

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...

Detailed Description

Generic interface for simple recommenders

Member Function Documentation

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

It is up to the recommender implementor to decide when a prediction is useful, and to document it accordingly.

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, ExternalItemRecommender, ExternalRatingPredictor, BiPolarSlopeOne, Recommender, SlopeOne, Constant, GlobalAverage, UserAverage, ItemAverage, and Random.

void LoadModel

(

string

filename

)

Get the model parameters from a file

Parameters

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.

float Predict	(	int	user_id,
		int	item_id
	)

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 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.

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

Parameters

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

Returns

a sorted list of (item_id, score) tuples

Implemented in WeightedEnsemble, and Ensemble.

void SaveModel

(

string

filename

)

Save the model parameters to a file

Parameters

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.

string ToString

(

)

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.

void Train

(

)

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

• IRecommender.cs