BiPolarSlopeOne Class Reference

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

Inheritance diagram for BiPolarSlopeOne:

List of all members.

Public Member Functions
virtual void	Add (int user_id, int item_id, double rating)
virtual void	AddItem (int item_id)
virtual void	AddUser (int user_id)
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
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 online updates
bool	UpdateUsers [get, set]
	true if users shall be updated when doing online updates

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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 engine does NOT support online updates. They would be easy to implement, though.

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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.

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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

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Property Documentation

int MaxItemID [get, set, inherited]

Maximum item ID.

Maximum item ID

virtual double MaxRating [get, set, inherited]

The max rating value.

The max rating value

Implements IRatingPredictor.

int MaxUserID [get, set, inherited]

Maximum user ID.

Maximum user ID

virtual double MinRating [get, set, inherited]

The min rating value.

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 online updates

true if items shall be updated when doing online updates

bool UpdateUsers [get, set, inherited]

true if users shall be updated when doing online updates

true if users shall be updated when doing online updates

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

• BiPolarSlopeOne.cs