MyMediaLite  3.11
Public Member Functions | Properties | List of all members
Recommender Class Referenceabstract

Abstract recommender class implementing default behaviors More...

Inheritance diagram for Recommender:
IRecommender ItemRecommender RatingPredictor ExternalItemRecommender IncrementalItemRecommender MostPopularByAttributes Random Zero BiPolarSlopeOne CoClustering ExternalRatingPredictor FactorWiseMatrixFactorization IncrementalRatingPredictor LatentFeatureLogLinearModel SlopeOne TimeAwareRatingPredictor

Public Member Functions

virtual 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...
 
Object Clone ()
 create a shallow copy of the object More...
 
virtual void LoadModel (string file)
 Get the model parameters from a file More...
 
abstract 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...
 
virtual System.Collections.Generic.IList< Tuple< int, float > > Recommend (int user_id, int n=-1, System.Collections.Generic.ICollection< int > ignore_items=null, System.Collections.Generic.ICollection< int > candidate_items=null)
 
virtual void SaveModel (string file)
 Save the model parameters to a file More...
 
override string ToString ()
 Return a string representation of the recommender More...
 
abstract void Train ()
 Learn the model parameters of the recommender from the training data More...
 

Properties

int MaxItemID [get, set]
 Maximum item ID More...
 
int MaxUserID [get, set]
 Maximum user ID More...
 

Detailed Description

Abstract recommender class implementing default behaviors

Member Function Documentation

virtual bool CanPredict ( int  user_id,
int  item_id 
)
inlinevirtual

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

Implements IRecommender.

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

Object Clone ( )
inline

create a shallow copy of the object

virtual void LoadModel ( string  filename)
inlinevirtual
abstract float Predict ( int  user_id,
int  item_id 
)
pure virtual
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.

virtual void SaveModel ( string  filename)
inlinevirtual
override string ToString ( )
inline

Return a string representation of the recommender

The ToString() method of recommenders should list the class name and all hyperparameters, separated by space characters.

Implements IRecommender.

abstract void Train ( )
pure virtual

Property Documentation

int MaxItemID
getset

Maximum item ID

int MaxUserID
getset

Maximum user ID


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