IRatingPredictor Interface Reference

Interface for rating predictors. More...

Inheritance diagram for IRatingPredictor:
IRecommender IIncrementalRatingPredictor ITimeAwareRatingPredictor RatingPredictor IncrementalRatingPredictor TimeAwareRatingPredictor BiPolarSlopeOne CoClustering EntityAverage FactorWiseMatrixFactorization GlobalAverage IncrementalRatingPredictor SlopeOne TimeAwareRatingPredictor

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.
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.

Detailed Description

Interface for rating predictors.

Rating prediction is used in systems that let users rate items (e.g. movies, books, songs, etc.) on a certain scale, e.g. from 1 to 5 stars, where 1 star means the user does not like the item at all, and 5 stars mean the user likes the item very much.

Given an (incomplete) set of ratings for several items by several users (and maybe additional information), the task is to predict (some of the) missing ratings.

See also http://recsyswiki.com/wiki/Rating_prediction


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]
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.

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

Property Documentation

double MaxRating [get, set]

Gets or sets the maximum rating.

The maximally possible rating

Implemented in RatingPredictor.

double MinRating [get, set]

Gets or sets the minimum rating.

The minimally possible rating

Implemented in RatingPredictor.


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