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 MultiCoreBPRMF SoftMarginRankingMF WeightedBPRMF

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_id the user ID
item_id the 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_id the user ID
item_id the 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:
filename the name of the file to read from

Implements IRecommender.

Implemented in BPRLinear, BPRMF, KNN, MF, MostPopular, 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_id the user ID
item_id the item ID
Returns:
the predicted score/rating for the given user-item combination

Implements IRecommender.

Implemented in BPRLinear, BPRMF, ItemKNN, MF, MostPopular, Random, UserKNN, WeightedItemKNN, 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_id the user ID
item_id the 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_id the 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_id the 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:
filename the name of the file to write to

Implements IRecommender.

Implemented in BPRLinear, BPRMF, KNN, MF, MostPopular, 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 BPRLinear, BPRMF, ItemAttributeKNN, ItemKNN, MultiCoreBPRMF, SoftMarginRankingMF, UserAttributeKNN, UserKNN, WeightedBPRMF, WeightedItemKNN, WeightedUserKNN, and WRMF.


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:
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