Attribute-aware rating predictor using Naive Bayes More...

Inheritance diagram for NaiveBayes:

Public Member Functions
override void	AddRatings (IRatings ratings)
	Add new ratings and perform incremental training More...

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 More...

Object	Clone ()
	create a shallow copy of the object More...

override void	LoadModel (string filename)
	Get the model parameters from a file More...

	NaiveBayes ()
	Default constructor More...

override float	Predict (int user_id, int item_id)
	Predict rating or score for a given user-item combination More...

IList< Tuple< int, float > >	Recommend (int user_id, int n=-1, ICollection< int > ignore_items=null, ICollection< int > candidate_items=null)
	Recommend items for a given user More...

virtual System.Collections.Generic.IList< Tuple< int, float > >	Recommend (int user_id, int n=-1, System.Collections.Generic.ICollection< int > ignore_items=null, System.Collections.Generic.ICollection< int > candidate_items=null)

virtual void	RemoveItem (int item_id)
	Remove all feedback by one item More...

override void	RemoveRatings (IDataSet ratings)
	Remove existing ratings and perform "incremental" training More...

virtual void	RemoveUser (int user_id)
	Remove all feedback by one user More...

override void	SaveModel (string filename)
	Save the model parameters to a file More...

override string	ToString ()
	Return a string representation of the recommender More...

override void	Train ()
	Learn the model parameters of the recommender from the training data More...

override void	UpdateRatings (IRatings ratings)
	Update existing ratings and perform incremental training More...

Protected Member Functions
virtual void	AddItem (int item_id)

override void	AddUser (int user_id)

Protected Attributes
float	max_rating
	Maximum rating value More...

float	min_rating
	Minimum rating value More...

IRatings	ratings
	rating data More...

Properties
float	AttributeSmoothing `[get, set]`
	Smoothing parameter for the attribute (given class/rating) probabilities More...

float	ClassSmoothing `[get, set]`
	Smoothing parameter for the class probabilities (rating priors) More...

IBooleanMatrix	ItemAttributes `[get, set]`

int	MaxItemID `[get, set]`
	Maximum item ID More...

virtual float	MaxRating `[get, set]`
	Maximum rating value More...

int	MaxUserID `[get, set]`
	Maximum user ID More...

virtual float	MinRating `[get, set]`
	Minimum rating value More...

int	NumItemAttributes `[get]`

virtual IRatings	Ratings `[get, set]`
	The rating data More...

bool	UpdateItems `[get, set]`

bool	UpdateUsers `[get, set]`

Detailed Description

Attribute-aware rating predictor using Naive Bayes

This recommender supports incremental updates.

Constructor & Destructor Documentation

NaiveBayes ( )

inline

Default constructor

Member Function Documentation

override void AddRatings ( IRatings ratings )

inlinevirtual

Add new ratings and perform incremental training

Parameters

ratings the ratings

Reimplemented from IncrementalRatingPredictor.

virtual bool CanPredict	(	int	user_id,
		int	item_id
	)

inlinevirtualinherited

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.

Reimplemented in ExternalItemRecommender, ExternalRatingPredictor, BiPolarSlopeOne, SlopeOne, Constant, GlobalAverage, UserAverage, ItemAverage, and Random.

Object Clone ( )

inlineinherited

create a shallow copy of the object

override void LoadModel ( string filename )

inline

Get the model parameters from a file

Parameters

filename the name of the file to read from

Implements IRecommender.

override float Predict	(	int	user_id,
		int	item_id
	)

inline

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.

IList<Tuple<int, float> > Recommend	(	int	user_id,
		int	n = `-1`,
		ICollection< int >	ignore_items = `null`,
		ICollection< int >	candidate_items = `null`
	)

inherited

Recommend items for a given user

Parameters

user_id	the user ID
n	the number of items to recommend, -1 for as many as possible
ignore_items	collection if items that should not be returned; if null, use empty collection
candidate_items	the candidate items to choose from; if null, use all items

Returns: a sorted list of (item_id, score) tuples

Implemented in WeightedEnsemble, and Ensemble.

virtual void RemoveItem ( int item_id )

inlinevirtualinherited

Remove all feedback by one item

Parameters

item_id the item ID

Implements IIncrementalRecommender.

Reimplemented in BiasedMatrixFactorization, MatrixFactorization, and ItemAverage.

override void RemoveRatings ( IDataSet ratings )

inlinevirtual

Remove existing ratings and perform "incremental" training

Parameters

ratings the user and item IDs of the ratings to be removed

Reimplemented from IncrementalRatingPredictor.

virtual void RemoveUser ( int user_id )

inlinevirtualinherited

Remove all feedback by one user

Parameters

user_id the user ID

Implements IIncrementalRecommender.

Reimplemented in BiasedMatrixFactorization, MatrixFactorization, and UserAverage.

override void SaveModel ( string filename )

inline

Save the model parameters to a file

Parameters

filename the name of the file to write to

Implements IRecommender.

override string ToString ( )

inline

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.

override void Train ( )

inline

Learn the model parameters of the recommender from the training data

Implements IRecommender.

override void UpdateRatings ( IRatings ratings )

inlinevirtual

Update existing ratings and perform incremental training

Parameters

ratings the ratings

Reimplemented from IncrementalRatingPredictor.

Member Data Documentation

float max_rating

protectedinherited

Maximum rating value

float min_rating

protectedinherited

Minimum rating value

IRatings ratings

protectedinherited

rating data

Property Documentation

float AttributeSmoothing

getset

Smoothing parameter for the attribute (given class/rating) probabilities

float ClassSmoothing

getset

Smoothing parameter for the class probabilities (rating priors)

int MaxItemID

getsetinherited

Maximum item ID

virtual float MaxRating

getsetinherited

Maximum rating value

int MaxUserID

getsetinherited

Maximum user ID

virtual float MinRating

getsetinherited

Minimum rating value

virtual IRatings Ratings

getsetinherited

The rating data

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

NaiveBayes.cs

Public Member Functions

Protected Member Functions

Protected Attributes

Properties

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

Property Documentation