ITimeAwareRatingPredictor Interface Reference

Interface for time-aware rating predictors. More...

Inheritance diagram for ITimeAwareRatingPredictor:

List of all members.

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.
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.
double	Predict (int user_id, int item_id, DateTime time)
	predict rating at a certain point in time
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.
Properties
double	MaxRating [get, set]
	Gets or sets the maximum rating.
double	MinRating [get, set]
	Gets or sets the minimum rating.
ITimedRatings	TimedRatings [get, set]
	training data that also contains the time information

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Detailed Description

Interface for time-aware rating predictors.

Time-aware rating predictors use the information contained in the dates/times of the ratings to build more accurate models.

They may or may not use time information at prediction (as opposed to training) time.

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Member Function Documentation

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.

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]

Get the model parameters from a file.

Parameters:

filename

the name of the file to read from

Implemented in Ensemble, WeightedEnsemble, BPR_Linear, BPRMF, ItemRecommender, KNN, MF, MostPopular, Random, Zero, BiasedMatrixFactorization, BiPolarSlopeOne, CoClustering, EntityAverage, FactorWiseMatrixFactorization, GlobalAverage, ItemKNN, KNN, MatrixFactorization, RatingPredictor, SlopeOne, and UserItemBaseline.

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, CoClustering, FactorWiseMatrixFactorization, GlobalAverage, ItemAverage, ItemKNN, MatrixFactorization, RatingPredictor, SlopeOne, TimeAwareBaseline, UserAverage, UserItemBaseline, and UserKNN.

double Predict	(	int	user_id,
		int	item_id,
		DateTime	time
	)

predict rating at a certain point in time

Parameters:

	user_id	the user ID
	item_id	the item ID
	time	the time of the rating event

Implemented in TimeAwareBaseline, TimeAwareBaselineWithFrequencies, and TimeAwareRatingPredictor.

void SaveModel

(

string

filename

)

[inherited]

Save the model parameters to a file.

Parameters:

filename

the name of the file to write to

Implemented in Ensemble, WeightedEnsemble, BPR_Linear, BPRMF, ItemRecommender, KNN, MF, MostPopular, Random, Zero, BiasedMatrixFactorization, BiPolarSlopeOne, CoClustering, EntityAverage, FactorWiseMatrixFactorization, GlobalAverage, KNN, MatrixFactorization, RatingPredictor, SlopeOne, and UserItemBaseline.

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, ItemRecommender, UserAttributeKNN, UserKNN, WeightedItemKNN, WeightedUserKNN, WRMF, BiasedMatrixFactorization, CoClustering, FactorWiseMatrixFactorization, ItemAttributeKNN, ItemKNNCosine, ItemKNNPearson, MatrixFactorization, RatingPredictor, TimeAwareBaseline, TimeAwareBaselineWithFrequencies, UserAttributeKNN, UserItemBaseline, UserKNNCosine, and UserKNNPearson.

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Property Documentation

double MaxRating [get, set, inherited]

Gets or sets the maximum rating.

The maximally possible rating

Implemented in RatingPredictor.

double MinRating [get, set, inherited]

Gets or sets the minimum rating.

The minimally possible rating

Implemented in RatingPredictor.

ITimedRatings TimedRatings [get, set]

training data that also contains the time information

Implemented in TimeAwareRatingPredictor.

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

• ITimeAwareRatingPredictor.cs