MyMediaLite  3.04
Public Member Functions | Protected Member Functions | Properties
IncrementalItemRecommender Class Reference

Base class for item recommenders that support incremental updates. More...

Inheritance diagram for IncrementalItemRecommender:
ItemRecommender IIncrementalItemRecommender Recommender IIncrementalRecommender IRecommender MF MostPopular BPRMF CLiMF WRMF BPRMF_Mapping BPRMF_Mapping MultiCoreBPRMF SoftMarginRankingMF WeightedBPRMF BPRMF_ItemMapping BPRMF_UserMapping BPRMF_ItemMapping_Optimal BPRMF_ItemMappingKNN BPRMF_ItemMappingSVR BPRMF_UserMapping_Optimal

List of all members.

Public Member Functions

virtual void AddFeedback (ICollection< Tuple< int, int >> feedback)
 Add positive feedback events and perform incremental training.
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.
Object Clone ()
 create a shallow copy of the object
virtual void LoadModel (string file)
 Get the model parameters from a file.
abstract 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.
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 RemoveFeedback (ICollection< Tuple< int, int >> feedback)
 Remove all feedback events by the given user-item combinations.
virtual void RemoveItem (int item_id)
 Remove all feedback by one item.
virtual void RemoveUser (int user_id)
 Remove all feedback by one user.
virtual void SaveModel (string file)
 Save the model parameters to a file.
override string ToString ()
 Return a string representation of the recommender.
abstract void Train ()
 Learn the model parameters of the recommender from the training data.

Protected Member Functions

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

Properties

virtual IPosOnlyFeedback Feedback [get, set]
 the feedback data to be used for training
int MaxItemID [get, set]
 Maximum item ID.
int MaxUserID [get, set]
 Maximum user ID.
bool UpdateItems [get, set]
 true if items shall be updated when doing incremental updates
bool UpdateUsers [get, set]
 true if users shall be updated when doing incremental updates

Detailed Description

Base class for item recommenders that support incremental updates.


Member Function Documentation

virtual void AddFeedback ( ICollection< Tuple< int, int >>  feedback) [inline, virtual]

Add positive feedback events and perform incremental training.

Parameters:
feedbackcollection of user id - item id tuples

Implements IIncrementalItemRecommender.

Reimplemented in BPRMF, and MostPopular.

virtual bool CanPredict ( int  user_id,
int  item_id 
) [inline, virtual, 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

Implements IRecommender.

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

Object Clone ( ) [inline, inherited]

create a shallow copy of the object

virtual void LoadModel ( string  filename) [inline, virtual, inherited]
abstract float Predict ( int  user_id,
int  item_id 
) [pure virtual, 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.

virtual void RemoveFeedback ( ICollection< Tuple< int, int >>  feedback) [inline, virtual]

Remove all feedback events by the given user-item combinations.

Parameters:
feedbackcollection of user id - item id tuples

Implements IIncrementalItemRecommender.

Reimplemented in BPRMF, and MostPopular.

virtual void RemoveItem ( int  item_id) [inline, virtual]

Remove all feedback by one item.

Parameters:
item_idthe item ID

Implements IIncrementalRecommender.

Reimplemented in BPRMF, and MostPopular.

virtual void RemoveUser ( int  user_id) [inline, virtual]

Remove all feedback by one user.

Parameters:
user_idthe user ID

Implements IIncrementalRecommender.

Reimplemented in BPRMF, and MostPopular.

virtual void SaveModel ( string  filename) [inline, virtual, inherited]
override string ToString ( ) [inline, inherited]

Property Documentation

virtual IPosOnlyFeedback Feedback [get, set, inherited]

the feedback data to be used for training

int MaxItemID [get, set, inherited]

Maximum item ID.

int MaxUserID [get, set, inherited]

Maximum user ID.

bool UpdateItems [get, set]

true if items shall be updated when doing incremental updates

Set to false if you do not want any updates to the item model parameters when doing incremental updates.

Implements IIncrementalRecommender.

bool UpdateUsers [get, set]

true if users shall be updated when doing incremental updates

Default should be true. Set to false if you do not want any updates to the user model parameters when doing incremental updates.

Implements IIncrementalRecommender.


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