ItemAttributeKNN Class Reference

Attribute-aware weighted item-based kNN recommender. More...

Inheritance diagram for ItemAttributeKNN:

Public Member Functions
override void	Add (int user_id, int item_id, double rating)
override void	AddItem (int item_id)
override void	AddUser (int user_id)
virtual 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 filename)
	Get the model parameters from a file.
override double	Predict (int user_id, int item_id)
	Predict the rating of a given user for a given item.
virtual void	RemoveItem (int item_id)
override void	RemoveRating (int user_id, int item_id)
virtual void	RemoveUser (int user_id)
override void	SaveModel (string filename)
	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.
override void	UpdateRating (int user_id, int item_id, double rating)
Protected Member Functions
override void	InitModel ()
	Inits the recommender model.
virtual void	RetrainItem (int item_id)
virtual void	RetrainUser (int user_id)
Protected Attributes
CorrelationMatrix	correlation
	Correlation matrix over some kind of entity.
SparseBooleanMatrix	data_item
	Matrix indicating which item was rated by which user.
Func< int, IList< int > >	GetPositivelyCorrelatedEntities
	Get positively correlated entities.
double	max_rating
	The max rating value.
double	min_rating
	The min rating value.
IRatings	ratings
	rating data
Properties
SparseBooleanMatrix	ItemAttributes `[get, set]`
uint	K `[get, set]`
	Number of neighbors to take into account for predictions.
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.
int	NumItemAttributes `[get, set]`
override IRatings	Ratings `[set]`
	The rating data.
double	RegI `[get, set]`
	Regularization parameter for the item biases.
double	RegU `[get, set]`
	Regularization parameter for the user biases.
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

Detailed Description

Attribute-aware weighted item-based kNN recommender.

This engine does NOT support online updates.

Member Function Documentation

virtual bool CanPredict	(	int	user_id,
		int	item_id
	)			`[virtual, inherited]`

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

Implements IRecommender.

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

Object Clone ( ) [inherited]

create a shallow copy of the object

override void InitModel ( ) [protected, virtual, inherited]

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, inherited]

Get the model parameters from a file.

Parameters:

filename

the name of the file to read from

Reimplemented from KNN.

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

Predict the rating of a given user for a given item.

If the user or the item are not known to the engine, a suitable average is returned. To avoid this behavior for unknown entities, use CanPredict() to check before.

Parameters:

	user_id	the user ID
	item_id	the item ID

Returns:: the predicted rating

Reimplemented from UserItemBaseline.

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

Save the model parameters to a file.

Parameters:

filename

the name of the file to write to

Reimplemented from UserItemBaseline.

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

CorrelationMatrix correlation [protected, inherited]

Correlation matrix over some kind of entity.

SparseBooleanMatrix data_item [protected, inherited]

Matrix indicating which item was rated by which user.

Func<int, IList<int> > GetPositivelyCorrelatedEntities [protected, inherited]

Get positively correlated entities.

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

SparseBooleanMatrix ItemAttributes [get, set]

The binary item attributes

Implements IItemAttributeAwareRecommender.

uint K [get, set, inherited]

Number of neighbors to take into account for predictions.

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.

int NumItemAttributes [get, set]

an integer stating the number of attributes

Implements IItemAttributeAwareRecommender.

override IRatings Ratings [set, inherited]

The rating data.

Reimplemented from RatingPredictor.

double RegI [get, set, inherited]

Regularization parameter for the item biases.

If not set, the recommender will try to find suitable values.

double RegU [get, set, inherited]

Regularization parameter for the user biases.

If not set, the recommender will try to find suitable values.

bool UpdateItems [get, set, inherited]

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

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

RatingPrediction/ItemAttributeKNN.cs

ItemAttributeKNN Class Reference

Public Member Functions

Protected Member Functions

Protected Attributes

Properties

Detailed Description

Member Function Documentation

Member Data Documentation

Property Documentation