MyMediaLite  3.07
Public Member Functions
IFoldInItemRecommender Interface Reference

Item recommender that allows folding in new users. More...

Inheritance diagram for IFoldInItemRecommender:
IRecommender BPRMF UserKNN BPRMF_Mapping BPRMF_Mapping MultiCoreBPRMF SoftMarginRankingMF WeightedBPRMF UserAttributeKNN BPRMF_ItemMapping BPRMF_UserMapping BPRMF_ItemMapping_Optimal BPRMF_ItemMappingKNN BPRMF_ItemMappingSVR BPRMF_UserMapping_Optimal

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.
float Predict (int user_id, int item_id)
 Predict rating or score for a given user-item combination.
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.
void SaveModel (string filename)
 Save the model parameters to a file.
IList< Tuple< int, float > > ScoreItems (IList< int > accessed_items, IList< int > candidate_items)
 Score a list of items given a list of items that represent a new user.
string ToString ()
 Return a string representation of the recommender.
void Train ()
 Learn the model parameters of the recommender from the training data.

Detailed Description

Item recommender that allows folding in new users.

The process of folding in is computing a predictive model for a new user based on their feedback and the existing recommender, without modifying the parameters of the existing recommender.

Literature:


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_idthe user ID
item_idthe 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) [inherited]
float Predict ( int  user_id,
int  item_id 
) [inherited]
IList<Tuple<int, float> > Recommend ( int  user_id,
int  n = -1,
ICollection< int >  ignore_items = null,
ICollection< int >  candidate_items = null 
) [inherited]

Recommend items for a given user.

Parameters:
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
Returns:
a sorted list of (item_id, score) tuples

Implemented in WeightedEnsemble, and Ensemble.

void SaveModel ( string  filename) [inherited]
IList<Tuple<int, float> > ScoreItems ( IList< int >  accessed_items,
IList< int >  candidate_items 
)

Score a list of items given a list of items that represent a new user.

Returns:
a list of int and float pairs, representing item IDs and predicted scores
Parameters:
accessed_itemsthe ratings (item IDs and rating values) representing the new user
candidate_itemsthe items to be rated

Implemented in BPRMF, and UserKNN.

string ToString ( ) [inherited]

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