MyMediaLite  3.11
Public Member Functions | Protected Member Functions | Protected Attributes | Properties | List of all members
Random Class Reference

Uses a random rating value for prediction More...

Inheritance diagram for Random:
IncrementalRatingPredictor RatingPredictor IIncrementalRatingPredictor Recommender IRatingPredictor IRatingPredictor IIncrementalRecommender IRecommender IRecommender IRecommender

Public Member Functions

virtual void AddRatings (IRatings new_ratings)
 Add new ratings and perform incremental training More...
 
override 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...
 
override void LoadModel (string filename)
 Get the model parameters from a file More...
 
override 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 RemoveItem (int item_id)
 Remove all feedback by one item More...
 
virtual void RemoveRatings (IDataSet ratings_to_delete)
 Remove existing ratings and perform "incremental" training More...
 
virtual void RemoveUser (int user_id)
 Remove all feedback by one user More...
 
override void SaveModel (string filename)
 Save the model parameters to a file More...
 
override string ToString ()
 Return a string representation of the recommender More...
 
override void Train ()
 Learn the model parameters of the recommender from the training data More...
 
virtual void UpdateRatings (IRatings new_ratings)
 Update existing ratings and perform incremental training More...
 

Protected Member Functions

virtual void AddItem (int item_id)
 
virtual void AddUser (int user_id)
 

Protected Attributes

float max_rating
 Maximum rating value More...
 
float min_rating
 Minimum rating value More...
 
IRatings ratings
 rating data More...
 

Properties

int MaxItemID [get, set]
 Maximum item ID More...
 
virtual float MaxRating [get, set]
 Maximum rating value More...
 
int MaxUserID [get, set]
 Maximum user ID More...
 
virtual float MinRating [get, set]
 Minimum rating value More...
 
virtual IRatings Ratings [get, set]
 The rating data More...
 
bool UpdateItems [get, set]
 
bool UpdateUsers [get, set]
 

Detailed Description

Uses a random rating value for prediction

This recommender supports incremental updates. Updates are just ignored, because the predictions are always uniformly sampled from the interval of rating values.

Member Function Documentation

virtual void AddRatings ( IRatings  ratings)
inlinevirtualinherited

Add new ratings and perform incremental training

Parameters
ratingsthe ratings

Implements IIncrementalRatingPredictor.

Reimplemented in MatrixFactorization, UserItemBaseline, NaiveBayes, ItemKNN, UserKNN, UserAverage, GlobalAverage, and ItemAverage.

override 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

Reimplemented from Recommender.

Object Clone ( )
inlineinherited

create a shallow copy of the object

override void LoadModel ( string  filename)
inlinevirtual

Get the model parameters from a file

Parameters
filenamethe name of the file to read from

Reimplemented from Recommender.

override float Predict ( int  user_id,
int  item_id 
)
inlinevirtual

Predict rating or score for a given user-item combination

Parameters
user_idthe user ID
item_idthe item ID
Returns
the predicted score/rating for the given user-item combination

Implements Recommender.

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 RemoveItem ( int  item_id)
inlinevirtualinherited

Remove all feedback by one item

Parameters
item_idthe item ID

Implements IIncrementalRecommender.

Reimplemented in BiasedMatrixFactorization, MatrixFactorization, and ItemAverage.

virtual void RemoveRatings ( IDataSet  ratings)
inlinevirtualinherited

Remove existing ratings and perform "incremental" training

Parameters
ratingsthe user and item IDs of the ratings to be removed

Implements IIncrementalRatingPredictor.

Reimplemented in MatrixFactorization, UserItemBaseline, NaiveBayes, ItemKNN, UserKNN, UserAverage, ItemAverage, and GlobalAverage.

virtual void RemoveUser ( int  user_id)
inlinevirtualinherited

Remove all feedback by one user

Parameters
user_idthe user ID

Implements IIncrementalRecommender.

Reimplemented in BiasedMatrixFactorization, MatrixFactorization, and UserAverage.

override void SaveModel ( string  filename)
inlinevirtual

Save the model parameters to a file

Parameters
filenamethe name of the file to write to

Reimplemented from Recommender.

override string ToString ( )
inlineinherited

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.

override void Train ( )
inlinevirtual

Learn the model parameters of the recommender from the training data

Implements Recommender.

virtual void UpdateRatings ( IRatings  ratings)
inlinevirtualinherited

Update existing ratings and perform incremental training

Parameters
ratingsthe ratings

Implements IIncrementalRatingPredictor.

Reimplemented in MatrixFactorization, UserItemBaseline, NaiveBayes, ItemKNN, UserKNN, UserAverage, GlobalAverage, and ItemAverage.

Member Data Documentation

float max_rating
protectedinherited

Maximum rating value

float min_rating
protectedinherited

Minimum rating value

IRatings ratings
protectedinherited

rating data

Property Documentation

int MaxItemID
getsetinherited

Maximum item ID

virtual float MaxRating
getsetinherited

Maximum rating value

int MaxUserID
getsetinherited

Maximum user ID

virtual float MinRating
getsetinherited

Minimum rating value

virtual IRatings Ratings
getsetinherited

The rating data


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