MyMediaLite  3.01
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 IRecommender IRecommender MF MostPopular BPRMF 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 (int user_id, int item_id)
 Add a positive feedback event 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
abstract void LoadModel (string filename)
 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.
virtual void RemoveFeedback (int user_id, int item_id)
 Remove all feedback events by the given user-item combination.
virtual void RemoveItem (int item_id)
 Remove all feedback by one item.
virtual void RemoveUser (int user_id)
 Remove all feedback by one user.
abstract void SaveModel (string filename)
 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.

Detailed Description

Base class for item recommenders that support incremental updates.


Member Function Documentation

virtual void AddFeedback ( int  user_id,
int  item_id 
) [inline, virtual]

Add a positive feedback event and perform incremental training.

Parameters:
user_idthe user ID
item_idthe item ID

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.

Object Clone ( ) [inline, inherited]

create a shallow copy of the object

abstract void LoadModel ( string  filename) [pure virtual, inherited]

Get the model parameters from a file.

Parameters:
filenamethe name of the file to read from

Implements IRecommender.

Implemented in BPRMF, BPRLinear, ItemAttributeSVM, MF, MostPopularByAttributes, MostPopular, KNN, Random, and Zero.

abstract float Predict ( int  user_id,
int  item_id 
) [pure virtual, inherited]

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 IRecommender.

Implemented in BPRMF, BPRMF_ItemMapping, BPRLinear, BPRMF_UserMapping, ItemAttributeSVM, MF, MostPopularByAttributes, MostPopular, UserKNN, ItemKNN, WeightedItemKNN, Random, WeightedUserKNN, and Zero.

virtual void RemoveFeedback ( int  user_id,
int  item_id 
) [inline, virtual]

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

Parameters:
user_idthe user ID
item_idthe item ID

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 IIncrementalItemRecommender.

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 IIncrementalItemRecommender.

Reimplemented in BPRMF, and MostPopular.

abstract void SaveModel ( string  filename) [pure virtual, inherited]

Save the model parameters to a file.

Parameters:
filenamethe name of the file to write to

Implements IRecommender.

Implemented in BPRMF, BPRLinear, ItemAttributeSVM, MostPopularByAttributes, MF, MostPopular, KNN, Random, and Zero.

override string ToString ( ) [inline, inherited]

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.

Reimplemented in BPRMF, BPRMF_Mapping, BPRLinear, BPRMF_ItemMapping, BPRMF_UserMapping, WRMF, MultiCoreBPRMF, BPRMF_ItemMapping_Optimal, BPRMF_ItemMappingSVR, SoftMarginRankingMF, ItemAttributeSVM, BPRMF_UserMapping_Optimal, BPRMF_ItemMappingKNN, WeightedBPRMF, ItemKNN, UserKNN, ItemAttributeKNN, UserAttributeKNN, WeightedItemKNN, and WeightedUserKNN.


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.


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