BiPolarSlopeOne Class Reference

Bi-polar frequency-weighted Slope-One rating prediction. More...

Inheritance diagram for BiPolarSlopeOne:
RatingPredictor IRatingPredictor IRecommender

List of all members.

Public Member Functions

virtual void AddRating (int user_id, int item_id, double rating)
override bool CanPredict (int user_id, int item_id)
 Check whether a useful prediction can be made for a given user-item combination.
Object Clone ()
 create a shallow copy of the object
override void LoadModel (string file)
 Get the model parameters from a file.
override double Predict (int user_id, int item_id)
 Predict rating or score for a given user-item combination.
virtual void RemoveItem (int item_id)
virtual void RemoveRating (int user_id, int item_id)
virtual void RemoveUser (int user_id)
override void SaveModel (string file)
 Save the model parameters to a file.
override string ToString ()
 Return a string representation of the recommender.
override void Train ()
 Learn the model parameters of the recommender from the training data.
virtual void UpdateRating (int user_id, int item_id, double rating)

Protected Member Functions

virtual void AddItem (int item_id)
virtual void AddUser (int user_id)
override void InitModel ()
 Inits the recommender model.

Protected Attributes

double max_rating
 The max rating value.
double min_rating
 The min rating value.
IRatings ratings
 rating data

Properties

int MaxItemID [get, set]
 Maximum item ID.
virtual double MaxRating [get, set]
 The max rating value.
int MaxUserID [get, set]
 Maximum user ID.
virtual double MinRating [get, set]
 The min rating value.
virtual IRatings Ratings [get, set]
 The rating data.
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

Bi-polar frequency-weighted Slope-One rating prediction.

Daniel Lemire, Anna Maclachlan: Slope One Predictors for Online Rating-Based Collaborative Filtering. SIAM Data Mining (SDM 2005) http://www.daniel-lemire.com/fr/abstracts/SDM2005.html

This recommender does NOT support incremental updates. They would be easy to implement, though.


Member Function Documentation

override bool CanPredict ( int  user_id,
int  item_id 
) [virtual]

Check whether a useful prediction can be made for a given user-item combination.

Parameters:
user_id the user ID
item_id the item ID
Returns:
true if a useful prediction can be made, false otherwise

Reimplemented from RatingPredictor.

Object Clone (  )  [inherited]

create a shallow copy of the object

override void InitModel (  )  [protected, virtual]

Inits the recommender model.

This method is called by the Train() method. When overriding, please call base.InitModel() to get the functions performed in the base class.

Reimplemented from RatingPredictor.

override void LoadModel ( string  filename  )  [virtual]

Get the model parameters from a file.

Parameters:
filename the name of the file to read from

Implements RatingPredictor.

override double Predict ( int  user_id,
int  item_id 
) [virtual]

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 RatingPredictor.

override void SaveModel ( string  filename  )  [virtual]

Save the model parameters to a file.

Parameters:
filename the name of the file to write to

Implements RatingPredictor.

override string ToString (  ) 

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.


Member Data Documentation

double max_rating [protected, inherited]

The max rating value.

double min_rating [protected, inherited]

The min rating value.

IRatings ratings [protected, inherited]

rating data


Property Documentation

int MaxItemID [get, set, inherited]

Maximum item ID.

virtual double MaxRating [get, set, inherited]

The max rating value.

Implements IRatingPredictor.

int MaxUserID [get, set, inherited]

Maximum user ID.

virtual double MinRating [get, set, inherited]

The min rating value.

Implements IRatingPredictor.

virtual IRatings Ratings [get, set, inherited]

The rating data.

Reimplemented in ItemKNN, and UserKNN.

bool UpdateItems [get, set, inherited]

true if items shall be updated when doing incremental updates

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

bool UpdateUsers [get, set, inherited]

true if users shall be updated when doing incremental updates

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


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