MyMediaLite  3.11
Public Member Functions | Properties | List of all members
IRatingPredictor Interface Reference

Interface for rating predictors More...

Inheritance diagram for IRatingPredictor:
IRecommender IFoldInRatingPredictor IIncrementalRatingPredictor ITimeAwareRatingPredictor ITransductiveRatingPredictor RatingPredictor ItemKNN MatrixFactorization UserAverage UserKNN IncrementalRatingPredictor TimeAwareRatingPredictor SigmoidCombinedAsymmetricFactorModel SigmoidItemAsymmetricFactorModel SigmoidSVDPlusPlus SigmoidUserAsymmetricFactorModel SVDPlusPlus BiPolarSlopeOne CoClustering ExternalRatingPredictor FactorWiseMatrixFactorization IncrementalRatingPredictor LatentFeatureLogLinearModel SlopeOne TimeAwareRatingPredictor

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...


float MaxRating [get, set]
 Gets or sets the maximum rating. More...
float MinRating [get, set]
 Gets or sets the minimum rating. More...
IRatings Ratings [get, set]
 the ratings to learn from More...

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

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.

user_idthe user ID
item_idthe item ID
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)
float Predict ( int  user_id,
int  item_id 
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

user_idthe user ID
nthe number of items to recommend, -1 for as many as possible
ignore_itemscollection if items that should not be returned; if null, use empty collection
candidate_itemsthe candidate items to choose from; if null, use all items
a sorted list of (item_id, score) tuples

Implemented in WeightedEnsemble, and Ensemble.

void SaveModel ( string  filename)
string ToString ( )
void Train ( )

Property Documentation

float MaxRating

Gets or sets the maximum rating.

The maximally possible rating

float MinRating

Gets or sets the minimum rating.

The minimally possible rating

IRatings Ratings

the ratings to learn from

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